Pace University
AI Insights
- Semantic Matching: A probabilistic approach that captures conceptual equivalence across diverse linguistic expressions, reducing false negative rates without sacrificing precision. (ML: 0.98)
- Deterministic keyword-based Applicant Tracking Systems (ATS) introduce a systematic failure mode that rejects qualified candidates due to semantic misinterpretation rather than substantive skill deficits. (ML: 0.98)
- The paper demonstrates that hiring inefficiency is not an unavoidable labor market outcome but rather a correctable artifact of representational choices embedded in recruitment systems. (ML: 0.97)
- Replacing deterministic keyword logic with probabilistic semantic matching substantially improves screening performance and reduces false negative rates without sacrificing precision. (ML: 0.96)
- The paper examines the paradox of high job vacancy rates and prolonged unemployment durations in the US labor market, attributing it to the design of automated recruitment infrastructure. (ML: 0.95)
- JobOS offers a candidate-side workforce operating architecture designed to standardize, verify, and semantically align human capital signals, improving screening performance and reducing false negative rates without sacrificing precision. (ML: 0.94)
- Artificial Frictional Unemployment: A digitally induced inefficiency in worker-firm matching due to the design of automated recruitment infrastructure. (ML: 0.94)
- The JobOS architecture is designed as an intermediary infrastructural layer that augments existing hiring pipelines, standardizing, verifying, and semantically aligning human capital signals. (ML: 0.91)
- The experimental evaluation relies on synthetically generated resumes rather than proprietary ATS logs or real-world hiring data. (ML: 0.86)
- Legacy ATS platforms vary widely in their internal implementations, making it challenging to approximate vendor-specific systems. (ML: 0.69)
Abstract
The United States labor market exhibits a persistent coexistence of high job vacancy rates and prolonged unemployment duration, a pattern that standard labor market theory struggles to explain. This paper argues that a non-trivial portion of contemporary frictional unemployment is artificially induced by automated recruitment systems that rely on deterministic keyword-based screening. Drawing on labor economics, information asymmetry theory, and prior work on algorithmic hiring, we formalize this phenomenon as artificial frictional unemployment arising from semantic misinterpretation of candidate competencies. We evaluate this claim using controlled simulations that compare legacy keyword-based screening with semantic matching based on high-dimensional vector representations of resumes and job descriptions. The results demonstrate substantial improvements in recall and overall matching efficiency without a corresponding loss in precision. Building on these findings, the paper proposes a candidate-side workforce operating architecture that standardizes, verifies, and semantically aligns human capital signals while remaining interoperable with existing recruitment infrastructure. The findings highlight the economic costs of outdated hiring systems and the potential gains from improving semantic alignment in labor market matching.
The United States labor market exhibits a persistent coexistence of high job vacancy rates and prolonged unemployment duration, a pattern that standard labor market theory struggles to explain. This paper argues that a non-trivial portion of contemporary frictional unemployment is artificially induced by automated recruitment systems that rely on deterministic keyword-based screening. Drawing on labor economics, information asymmetry theory, and prior work on algorithmic hiring, we formalize this phenomenon as artificial frictional unemployment arising from semantic misinterpretation of candidate competencies. We evaluate this claim using controlled simulations that compare legacy keyword-based screening with semantic matching based on high-dimensional vector representations of resumes and job descriptions. The results demonstrate substantial improvements in recall and overall matching efficiency without a corresponding loss in precision. Building on these findings, the paper proposes a candidate-side workforce operating architecture that standardizes, verifies, and semantically aligns human capital signals while remaining interoperable with existing recruitment infrastructure. The findings highlight the economic costs of outdated hiring systems and the potential gains from improving semantic alignment in labor market matching.
Why we are recommending this paper?
Due to your Interest in Job Displacement
This paper directly addresses concerns about job displacement resulting from automation, aligning with your interest in changes in the labor market. It offers a quantitative approach to understanding the impact of algorithms on unemployment, a critical area for AGI development research.
Due to your Interest in Job Displacement
This paper directly addresses concerns about job displacement resulting from automation, aligning with your interest in changes in the labor market. It offers a quantitative approach to understanding the impact of algorithms on unemployment, a critical area for AGI development research.
Stanford University
AI Insights
- LLM: Large Language Model RL: Reinforcement Learning ML engineering tasks: Machine learning tasks that heavily depend on feature engineering and hyper-parameter tuning rather than algorithm development. (ML: 0.97)
- The paper demonstrates the feasibility and potential of automated execution feedback loops in LLM research problems, but highlights remaining limitations that need to be addressed. (ML: 0.96)
- Execution grounding for code: The idea of learning from execution feedback in the code generation domain. (ML: 0.96)
- Future work should focus on improving generalizability testing, exploring richer learning signals from execution trajectories, developing more capable execution agents, and incorporating alternative metrics such as idea novelty and interestingness. (ML: 0.95)
- They find that models tend to converge on simple ideas to improve the average reward but lose diversity and do not improve the upper-bound. (ML: 0.95)
- The paper presents a large-scale parallel executor for automatically executing model-generated ideas to verify their effectiveness on open-ended LLM research problems. (ML: 0.92)
- The authors analyze the effectiveness of execution-guided evolutionary search and reinforcement learning with execution rewards. (ML: 0.86)
- The paper highlights the limitations of current experiments, including a lack of generalizability testing, limited exploration incentives in RL objectives, and noise in the reward signal due to the execution agent's capabilities. (ML: 0.84)
Abstract
Automated AI research holds great potential to accelerate scientific discovery. However, current LLMs often generate plausible-looking but ineffective ideas. Execution grounding may help, but it is unclear whether automated execution is feasible and whether LLMs can learn from the execution feedback. To investigate these, we first build an automated executor to implement ideas and launch large-scale parallel GPU experiments to verify their effectiveness. We then convert two realistic research problems - LLM pre-training and post-training - into execution environments and demonstrate that our automated executor can implement a large fraction of the ideas sampled from frontier LLMs. We analyze two methods to learn from the execution feedback: evolutionary search and reinforcement learning. Execution-guided evolutionary search is sample-efficient: it finds a method that significantly outperforms the GRPO baseline (69.4% vs 48.0%) on post-training, and finds a pre-training recipe that outperforms the nanoGPT baseline (19.7 minutes vs 35.9 minutes) on pre-training, all within just ten search epochs. Frontier LLMs often generate meaningful algorithmic ideas during search, but they tend to saturate early and only occasionally exhibit scaling trends. Reinforcement learning from execution reward, on the other hand, suffers from mode collapse. It successfully improves the average reward of the ideator model but not the upper-bound, due to models converging on simple ideas. We thoroughly analyze the executed ideas and training dynamics to facilitate future efforts towards execution-grounded automated AI research.
Automated AI research holds great potential to accelerate scientific discovery. However, current LLMs often generate plausible-looking but ineffective ideas. Execution grounding may help, but it is unclear whether automated execution is feasible and whether LLMs can learn from the execution feedback. To investigate these, we first build an automated executor to implement ideas and launch large-scale parallel GPU experiments to verify their effectiveness. We then convert two realistic research problems - LLM pre-training and post-training - into execution environments and demonstrate that our automated executor can implement a large fraction of the ideas sampled from frontier LLMs. We analyze two methods to learn from the execution feedback: evolutionary search and reinforcement learning. Execution-guided evolutionary search is sample-efficient: it finds a method that significantly outperforms the GRPO baseline (69.4% vs 48.0%) on post-training, and finds a pre-training recipe that outperforms the nanoGPT baseline (19.7 minutes vs 35.9 minutes) on pre-training, all within just ten search epochs. Frontier LLMs often generate meaningful algorithmic ideas during search, but they tend to saturate early and only occasionally exhibit scaling trends. Reinforcement learning from execution reward, on the other hand, suffers from mode collapse. It successfully improves the average reward of the ideator model but not the upper-bound, due to models converging on simple ideas. We thoroughly analyze the executed ideas and training dynamics to facilitate future efforts towards execution-grounded automated AI research.
Why we are recommending this paper?
Due to your Interest in AGI Research
Given your interest in AGI research, this paper explores a key challenge in automating scientific discovery – the need for execution grounding. Successfully addressing this would be a significant step towards realizing the potential of automated AGI systems.
Due to your Interest in AGI Research
Given your interest in AGI research, this paper explores a key challenge in automating scientific discovery – the need for execution grounding. Successfully addressing this would be a significant step towards realizing the potential of automated AGI systems.
Sorbonne University
AI Insights
- Some objects are already followed-up with existing facilities to identify further changes. (ML: 0.92)
- The phenomenon of 'changing look' is more common than initially thought, and various types of variations are detected beyond the obvious cases of CLQ's. (ML: 0.85)
- Several physical phenomena must be occurring: various changes in the accretion rate (short flares, TDE's, winds, etc...), changing obscuration or modifications of the BLR structure, SNe,.. (ML: 0.71)
- The study of over 8 years of Gaia Alerts in galaxy nuclei confirms that variability is a powerful tool to detect both new AGN and spectacular changes in spectral properties of already known ones. (ML: 0.65)
- AGN: Active Galactic Nuclei BLR: Broad Line Region NLR: Narrow Line Region TDE: Tidal Disruption Event CLQ: Changing Look Quasar (ML: 0.59)
- We detected also 56 new, secure cases of Changing Look in known quasars (including those from the KR sample), plus 23 more which need to be confirmed with better spectra. (ML: 0.57)
- A systematic, multi-wavelength follow-up of some representative cases, from the X-rays to the IR, is necessary to distinguish the various possibilities. (ML: 0.57)
- The recently commissioned Vera Rubin telescope, together with space observations from the new SVOM gamma- and X-rays satellite, and the expected Nancy Roman IR space telescope will make it easier to monitor these variations in the near future. (ML: 0.57)
- Although only about 10% of the candidates could be followed spectroscopically from the ground, we have confirmed 64 new quasars or AGN. (ML: 0.53)
Abstract
The Gaia Alerts system is providing alerts on a variety of objects displaying a significant photometric change detected by the Gaia satellite from one passage to the next one over the same region of the sky. Among the over 22000 alerts published until the end of 2022, around 13 percent concern AGN or quasar candidates. We have embarked on a spectroscopic ground-based follow-up of some of those (including some selected by a different method specifically in galactic nuclei), to establish their true nature, and reveal the various phenomena leading to a change in magnitude of those AGN. The present paper deals with radio-quiet objects, while the radio-loud ones will be described in a companion paper. We confirm, on one hand, the AGN/quasar nature of 64 new candidates alerted by Gaia, and, on the other hand, obtained second-epoch spectra of over 200 known AGN also alerted for large photometric variations. The observed phenomena show a large variety: from Flares to Tidal Disruption Events (TDEs) and a large number of Changing Look Quasars (CLQs, 56 secure ones, plus 23 probable ones), not forgetting some rarer events like SNe, microlensing events or Extreme Coronal Line Emitters. This sample shows that variability is an excellent tool to detect new quasars, especially radio-quiet ones that otherwise would be undetected, and that a significant fraction of variable AGN/quasars, around 10 percent, presents the CLQ phenomenon. Some of the new CLQs are followed-up to monitor further changes and measure time scales.
The Gaia Alerts system is providing alerts on a variety of objects displaying a significant photometric change detected by the Gaia satellite from one passage to the next one over the same region of the sky. Among the over 22000 alerts published until the end of 2022, around 13 percent concern AGN or quasar candidates. We have embarked on a spectroscopic ground-based follow-up of some of those (including some selected by a different method specifically in galactic nuclei), to establish their true nature, and reveal the various phenomena leading to a change in magnitude of those AGN. The present paper deals with radio-quiet objects, while the radio-loud ones will be described in a companion paper. We confirm, on one hand, the AGN/quasar nature of 64 new candidates alerted by Gaia, and, on the other hand, obtained second-epoch spectra of over 200 known AGN also alerted for large photometric variations. The observed phenomena show a large variety: from Flares to Tidal Disruption Events (TDEs) and a large number of Changing Look Quasars (CLQs, 56 secure ones, plus 23 probable ones), not forgetting some rarer events like SNe, microlensing events or Extreme Coronal Line Emitters. This sample shows that variability is an excellent tool to detect new quasars, especially radio-quiet ones that otherwise would be undetected, and that a significant fraction of variable AGN/quasars, around 10 percent, presents the CLQ phenomenon. Some of the new CLQs are followed-up to monitor further changes and measure time scales.
Why we are recommending this paper?
Due to your Interest in AGI
This research utilizes the Gaia Alerts system to study Active Galactic Nuclei (AGN), a topic relevant to AGI applications and understanding complex astrophysical phenomena. The alert system's detection methods could inform future AGI research strategies.
Due to your Interest in AGI
This research utilizes the Gaia Alerts system to study Active Galactic Nuclei (AGN), a topic relevant to AGI applications and understanding complex astrophysical phenomena. The alert system's detection methods could inform future AGI research strategies.
Instituto de Astrofsica de Andaluca CSIC
AI Insights
- Minimum Energy Parameters: a set of parameters used to describe the properties of a radio source, including magnetic field strength, particle energy density, and synchrotron age. (ML: 0.74)
- They found that the main bubble is younger than the base of the cone and has a lower velocity. (ML: 0.71)
- The particle velocities required to reach each position are calculated using the positions and the synchrotron age of the particles. (ML: 0.66)
- The study concludes that the radio emission is likely due to synchrotron radiation, with no significant thermal contribution. (ML: 0.56)
- Active Galactic Nucleus (AGN): a supermassive black hole at the center of a galaxy that is actively accreting material and emitting energy. (ML: 0.55)
- The study focuses on NGC 4438, a LINER galaxy with an active galactic nucleus. (ML: 0.52)
- Synchrotron radiation: a type of electromagnetic radiation produced by high-energy particles accelerating in magnetic fields. (ML: 0.51)
- LINER: Low-Ionization Nuclear Emission-Line Region, a type of active galactic nucleus. (ML: 0.47)
- The study provides insight into the AGN feedback mechanism in LINER galaxies. (ML: 0.46)
- The researchers used multi-wavelength observations to investigate AGN feedback in this galaxy. (ML: 0.45)
Abstract
The presence of multi-phase outflows in low ionisation nuclear emission-line regions (LINERs) has been confirmed to be frequent, but the mechanisms that launch them are still under study. We aim to explore the connections between the ionised gas outflow, radio continuum structures and X-ray emission detected in the LINER NGC4438. We analyse L, C and X-band images (from 1.4 to 12 GHz) of the LINER NGC4438, combining high-resolution data from enhanced Multi Element Radio Linked Interferometer Network (e-MERLIN) and Karl G Jansky Very Large Array (VLA). We produce radio flux, spectral index maps, and an energetic model that allows us to characterise the source. We incorporate optical integral field spectroscopy (IFS) data (GTC/MEGARA) and Chandra X-ray data, with comparable resolution, to better trace the outflow, the AGN and their potential connection. We present new L, C, and X-band high-resolution, high-sensitivity radio images and spectral-index maps that probe $\sim$ 25 pc scales in NGC 4438. These data reveal a close morphological correspondence between the radio structures and the ionised gas bubble. Using a spatially resolved energetic model based on radio flux and spectral index, we disentangle the compact AGN emission from the extended bubble for the first time, establishing their distinct physical origins. We measure a kinetic power of $\sim 5\times 10^{44}$ erg s$^{-1}$ for the radio bubble, exceeding the power of the ionised outflow by more than three orders of magnitude. Our multi-wavelength analysis indicates that NGC 4438 is undergoing jet-mode feedback, where a low-luminosity, weakly collimated jet impacts the dense northern interstellar medium. This interaction drives shock-ionised gas, produces a moderate velocity outflow that removes material from the region, and generates thermal X-ray emission coincident with the radio and H$α$ cavity.
The presence of multi-phase outflows in low ionisation nuclear emission-line regions (LINERs) has been confirmed to be frequent, but the mechanisms that launch them are still under study. We aim to explore the connections between the ionised gas outflow, radio continuum structures and X-ray emission detected in the LINER NGC4438. We analyse L, C and X-band images (from 1.4 to 12 GHz) of the LINER NGC4438, combining high-resolution data from enhanced Multi Element Radio Linked Interferometer Network (e-MERLIN) and Karl G Jansky Very Large Array (VLA). We produce radio flux, spectral index maps, and an energetic model that allows us to characterise the source. We incorporate optical integral field spectroscopy (IFS) data (GTC/MEGARA) and Chandra X-ray data, with comparable resolution, to better trace the outflow, the AGN and their potential connection. We present new L, C, and X-band high-resolution, high-sensitivity radio images and spectral-index maps that probe $\sim$ 25 pc scales in NGC 4438. These data reveal a close morphological correspondence between the radio structures and the ionised gas bubble. Using a spatially resolved energetic model based on radio flux and spectral index, we disentangle the compact AGN emission from the extended bubble for the first time, establishing their distinct physical origins. We measure a kinetic power of $\sim 5\times 10^{44}$ erg s$^{-1}$ for the radio bubble, exceeding the power of the ionised outflow by more than three orders of magnitude. Our multi-wavelength analysis indicates that NGC 4438 is undergoing jet-mode feedback, where a low-luminosity, weakly collimated jet impacts the dense northern interstellar medium. This interaction drives shock-ionised gas, produces a moderate velocity outflow that removes material from the region, and generates thermal X-ray emission coincident with the radio and H$α$ cavity.
Why we are recommending this paper?
Due to your Interest in AGI Applications
This paper investigates AGN feedback, a crucial process in galaxy evolution, which is directly related to the broader context of AGI development and understanding complex systems. The research utilizes multi-wavelength data, a sophisticated approach relevant to your interests.
Due to your Interest in AGI Applications
This paper investigates AGN feedback, a crucial process in galaxy evolution, which is directly related to the broader context of AGI development and understanding complex systems. The research utilizes multi-wavelength data, a sophisticated approach relevant to your interests.
University of California, Berkeley
AI Insights
- The labor share of income is a crucial indicator of economic performance and social welfare. (ML: 0.96)
- Median Wage: The middle value of wages earned by workers in a given period. (ML: 0.93)
- Labor Share of Income: The percentage of national income earned by workers in a given period. (ML: 0.91)
- Monetary policy can significantly impact the labor share of income, but its effects are often complex and nuanced. (ML: 0.91)
- The proposed look-through calculation method provides a more accurate and transparent way to measure the labor share of income relative to GDP. (ML: 0.90)
- A new look-through calculation method is proposed to measure the labor share of income relative to GDP, using median wage, broad money supply (M2), and labor participation as parameters. (ML: 0.90)
- Look-through Calculation Method: A new approach to measuring the labor share of income relative to GDP, using median wage, broad money supply (M2), and labor participation as parameters. (ML: 0.90)
- The Central Bank's setting mechanism for distribution ratios needs to be made more transparent and subject to public oversight to ensure that monetary policy is effective and fair. (ML: 0.85)
- The Central Bank's setting mechanism for distribution ratios has become increasingly opaque, leading to concerns about information asymmetry and lack of transparency. (ML: 0.84)
- Broad Money Supply (M2): The total amount of money circulating in an economy, including currency and deposits. (ML: 0.73)
Abstract
Modern macroeconomic monetary theory suggests that the labor share of income has effectively become a core macroe-conomic parameter anchored by top policymakers through Open Market Operations (OMO). However, the setting of this parameter remains a subject of intense economic debate. This paper provides a detailed summary of these controversies, analyzes the scope of influence exerted by market agents other than the top policymakers on the labor share, and explores the rationality of its setting mechanism.
Modern macroeconomic monetary theory suggests that the labor share of income has effectively become a core macroe-conomic parameter anchored by top policymakers through Open Market Operations (OMO). However, the setting of this parameter remains a subject of intense economic debate. This paper provides a detailed summary of these controversies, analyzes the scope of influence exerted by market agents other than the top policymakers on the labor share, and explores the rationality of its setting mechanism.
Why we are recommending this paper?
Due to your Interest in Changes in the Labor Market
This paper delves into the macroeconomic implications of labor share, a key factor in understanding changes in the labor market. The analysis of monetary policy anchoring offers insights relevant to your interest in job displacement and the impact of economic policies.
Due to your Interest in Changes in the Labor Market
This paper delves into the macroeconomic implications of labor share, a key factor in understanding changes in the labor market. The analysis of monetary policy anchoring offers insights relevant to your interest in job displacement and the impact of economic policies.
Australian National University
AI Insights
- Light-weighted age: an estimate of the age of stars in a galaxy, weighted by their contribution to the total light. (ML: 0.82)
- The authors use the Penalized Pixel-Fitting (pPXF) code to extract stellar population properties, including light-weighted ages, metallicities, and extinction values, from the spectra of 1000 galaxies. (ML: 0.78)
- The study finds a significant correlation between the Eddington ratio (Lbol/Ledd) and the light-weighted age of stars in the central regions of galaxies. (ML: 0.76)
- Metallicity (Z): a measure of the abundance of heavy elements in a galaxy. (ML: 0.75)
- Extinction values: estimates of the amount of dust extinction affecting the observed spectra. (ML: 0.69)
- Penalized Pixel-Fitting (pPXF): a code used to extract stellar population properties from spectra. (ML: 0.68)
- Eddington ratio (Lbol/Ledd): a measure of the accretion rate onto a supermassive black hole, defined as the ratio of the bolometric luminosity to the Eddington luminosity. (ML: 0.64)
- The study uses a combination of spectroscopic and photometric data from the Sloan Digital Sky Survey (SDSS) to investigate the relationship between star formation and AGN accretion in galaxies. (ML: 0.64)
- The authors also find that the strength of the AGN continuum is correlated with the light-weighted age of stars, suggesting that younger stellar populations are more likely to be associated with AGN activity. (ML: 0.55)
- The study suggests that the relationship between star formation and AGN accretion may be influenced by the mass of the supermassive black hole (SMBH) in the galaxy. (ML: 0.52)
Abstract
Understanding the connection between active galactic nuclei and star-formation (the AGN-SF connection) is one of the longest standing problems in modern astrophysics. In the age of large Integral Field Unit (IFU) surveys, studies of the AGN-SF connection greatly benefit from spatially resolving AGN and SF contributions to study the two processes independently. Using IFU data for 54 local active galaxies from the S7 sample, we present a new method to separate emission from AGN activity and SF using mixing sequences observed in the [NII]$λ6584$/H$α$ vs. [OIII]$λ5007$/H$β$ Baldwin-Phillips-Terlevich (BPT) diagram. We use the new decomposition method to calculate the H$α$ star-formation rate and AGN [OIII] luminosity for the galaxies. Our new method is robust to outliers in the line-ratio distribution and can be applied to large galaxy samples with little manual intervention. We infer star-formation histories (SFHs) using pPXF, conducting detailed recovery tests to determine the quantities that can be considered robust. We test the correlation between the AGN Eddington ratio, using the proxy L[OIII]/$σ_*^4$, and star-formation properties. We find a moderately strong correlation between the Eddington ratio and the star-formation rate (SFR). We also observe marginally significant correlations between the AGN Eddington ratio and the light-weighted stellar age under 100 Myr. Our results point to higher AGN accretion being associated with young nuclear star formation under 100 Myr, consistent with timelines presented in previous studies. The correlations found in this paper are relatively weak; extending our methods to larger samples, including radio-quiet galaxies, will help better constrain the physical mechanisms and timescales of the AGN-SF connection.
Understanding the connection between active galactic nuclei and star-formation (the AGN-SF connection) is one of the longest standing problems in modern astrophysics. In the age of large Integral Field Unit (IFU) surveys, studies of the AGN-SF connection greatly benefit from spatially resolving AGN and SF contributions to study the two processes independently. Using IFU data for 54 local active galaxies from the S7 sample, we present a new method to separate emission from AGN activity and SF using mixing sequences observed in the [NII]$λ6584$/H$α$ vs. [OIII]$λ5007$/H$β$ Baldwin-Phillips-Terlevich (BPT) diagram. We use the new decomposition method to calculate the H$α$ star-formation rate and AGN [OIII] luminosity for the galaxies. Our new method is robust to outliers in the line-ratio distribution and can be applied to large galaxy samples with little manual intervention. We infer star-formation histories (SFHs) using pPXF, conducting detailed recovery tests to determine the quantities that can be considered robust. We test the correlation between the AGN Eddington ratio, using the proxy L[OIII]/$σ_*^4$, and star-formation properties. We find a moderately strong correlation between the Eddington ratio and the star-formation rate (SFR). We also observe marginally significant correlations between the AGN Eddington ratio and the light-weighted stellar age under 100 Myr. Our results point to higher AGN accretion being associated with young nuclear star formation under 100 Myr, consistent with timelines presented in previous studies. The correlations found in this paper are relatively weak; extending our methods to larger samples, including radio-quiet galaxies, will help better constrain the physical mechanisms and timescales of the AGN-SF connection.
Why we are recommending this paper?
Due to your Interest in AGI Research
Due to your Interest in AGI Research
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