Every paper checked — nothing hidden

All papers

Every paper checked for brief #4 of 12–19 Oct 2026 — nothing is hidden. Brief papers first.

All17,313 In brief24 More (on-topic)3,333 Not relevant13,754 Not assessed87 Older352 Could not confirm93 Blogs with no paper266 All blogs284

Paper	Topic	Relevance
PrismaCoder: Pushing the Boundaries of Open Multimodal Code Intelligence through Decomposed Rubric Synthesis Introduces a decomposed rubric synthesis method to create training data for open multimodal models that generate visual code artifacts. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Focuses on data pipeline and training, not evaluation.
PrismaCoder: Pushing the Boundaries of Open Multimodal Code Intelligence through Decomposed Rubric Synthesis Introduces a decomposed rubric synthesis method to create training data for open multimodal models that generate visual code artifacts. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Does not focus on model compression or inference efficiency.
PrismaCoder: Pushing the Boundaries of Open Multimodal Code Intelligence through Decomposed Rubric Synthesis Introduces a decomposed rubric synthesis method to create training data for open multimodal models that generate visual code artifacts. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Visual code generation, not industrial manufacturing quality control.
PrismaCoder: Pushing the Boundaries of Open Multimodal Code Intelligence through Decomposed Rubric Synthesis Introduces a decomposed rubric synthesis method to create training data for open multimodal models that generate visual code artifacts. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Does not address safety, jailbreaks, or guardrails.
Detection of Potato Plant Leaf Diseases using Convolutional Neural Networks Develops and tests a lightweight convolutional neural network to classify potato leaf diseases on field-collected farm images. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Traditional compact CNN application, not SLMs or LLM efficiency.
Detection of Potato Plant Leaf Diseases using Convolutional Neural Networks Develops and tests a lightweight convolutional neural network to classify potato leaf diseases on field-collected farm images. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Does not address AI deployment safety or robustness.
Detection of Potato Plant Leaf Diseases using Convolutional Neural Networks Develops and tests a lightweight convolutional neural network to classify potato leaf diseases on field-collected farm images. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Applies existing metrics to leaf disease classification.
Detection of Potato Plant Leaf Diseases using Convolutional Neural Networks Develops and tests a lightweight convolutional neural network to classify potato leaf diseases on field-collected farm images. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Studies basic CNN classification, not autonomous language agents.
PerSo: Investigating Facets of LLMs' Social Intelligence in Real-World Persuasion Scenarios Introduces a benchmark based on real online discussions to evaluate both cognitive and behavioral persuasion skills in language models. Preprint	LLMs for code via arxiv · 15 Oct, 15:06	Not relevant Does not cover coding assistants or software repair.
PerSo: Investigating Facets of LLMs' Social Intelligence in Real-World Persuasion Scenarios Introduces a benchmark based on real online discussions to evaluate both cognitive and behavioral persuasion skills in language models. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Evaluates text-based dialogue, not multimodal models.
PerSo: Investigating Facets of LLMs' Social Intelligence in Real-World Persuasion Scenarios Introduces a benchmark based on real online discussions to evaluate both cognitive and behavioral persuasion skills in language models. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Benchmark paper evaluating persuasion dialogue rather than agent systems.
PerSo: Investigating Facets of LLMs' Social Intelligence in Real-World Persuasion Scenarios Introduces a benchmark based on real online discussions to evaluate both cognitive and behavioral persuasion skills in language models. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on persuasive capability evaluation rather than safety guardrails.
PerSo: Investigating Facets of LLMs' Social Intelligence in Real-World Persuasion Scenarios Introduces a benchmark based on real online discussions to evaluate both cognitive and behavioral persuasion skills in language models. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 15:06	Not relevant Does not involve external document retrieval or grounding.
PerSo: Investigating Facets of LLMs' Social Intelligence in Real-World Persuasion Scenarios Introduces a benchmark based on real online discussions to evaluate both cognitive and behavioral persuasion skills in language models. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Does not study model compression or efficient serving.
PhySGA: A Physics-Space Grounded Agentic Framework for Generalizable and Interactive 3D Composition Proposes an interactive agent framework that utilizes physics simulation and spatial exploration for complex 3D object assembly and composition. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on 3D graphics composition, not industrial inspection.
PhySGA: A Physics-Space Grounded Agentic Framework for Generalizable and Interactive 3D Composition Proposes an interactive agent framework that utilizes physics simulation and spatial exploration for complex 3D object assembly and composition. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Does not address AI safety or guardrails.
PhySGA: A Physics-Space Grounded Agentic Framework for Generalizable and Interactive 3D Composition Proposes an interactive agent framework that utilizes physics simulation and spatial exploration for complex 3D object assembly and composition. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Focuses on interactive composition framework, not benchmark methodology.
Scaling Discovery Requires Forgetting Shows that periodically clearing agent search history and restarting from the top candidate prevents automated research agents from plateauing. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Focuses on agent search strategies rather than benchmark design.
Scaling Discovery Requires Forgetting Shows that periodically clearing agent search history and restarting from the top candidate prevents automated research agents from plateauing. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Does not address model compression or efficient inference.
Scaling Discovery Requires Forgetting Shows that periodically clearing agent search history and restarting from the top candidate prevents automated research agents from plateauing. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 15:06	Not relevant Focuses on search state forgetting, not RAG.
Scaling Discovery Requires Forgetting Shows that periodically clearing agent search history and restarting from the top candidate prevents automated research agents from plateauing. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Does not involve multimodal data or models.
Scaling Discovery Requires Forgetting Shows that periodically clearing agent search history and restarting from the top candidate prevents automated research agents from plateauing. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Addresses search optimization rather than deployment safety risks.
Scaling Discovery Requires Forgetting Shows that periodically clearing agent search history and restarting from the top candidate prevents automated research agents from plateauing. Preprint	LLMs for code via arxiv · 15 Oct, 15:06	Not relevant General automated research optimization, not software engineering tools.
Recovering Reliable Supervision via Critique-Guided On-Policy Distillation Uses teacher critiques on incorrect student rollouts to improve on-policy distillation and recover supervision during mathematical reasoning tasks. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Focuses on distillation algorithms for reasoning, not agent workflows.
Recovering Reliable Supervision via Critique-Guided On-Policy Distillation Uses teacher critiques on incorrect student rollouts to improve on-policy distillation and recover supervision during mathematical reasoning tasks. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Addresses reasoning distillation rather than deployment safety or guardrails.
Recovering Reliable Supervision via Critique-Guided On-Policy Distillation Uses teacher critiques on incorrect student rollouts to improve on-policy distillation and recover supervision during mathematical reasoning tasks. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Proposes a training method rather than an evaluation framework.
One Task, Many Interfaces: Simple Cross-Interface Consistency Training Improves LLM Agent Robustness Introduces a self-supervised consistency loss across varied tool interfaces to make language model agents robust against notation and naming changes. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 15:06	Not relevant Focuses on agent interface robustness, not external document retrieval.
One Task, Many Interfaces: Simple Cross-Interface Consistency Training Improves LLM Agent Robustness Introduces a self-supervised consistency loss across varied tool interfaces to make language model agents robust against notation and naming changes. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Does not involve multimodal inputs like vision or audio.
One Task, Many Interfaces: Simple Cross-Interface Consistency Training Improves LLM Agent Robustness Introduces a self-supervised consistency loss across varied tool interfaces to make language model agents robust against notation and naming changes. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Proposes a training method, not a new evaluation benchmark.
One Task, Many Interfaces: Simple Cross-Interface Consistency Training Improves LLM Agent Robustness Introduces a self-supervised consistency loss across varied tool interfaces to make language model agents robust against notation and naming changes. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Does not focus on model compression, quantization, or distillation.
One Task, Many Interfaces: Simple Cross-Interface Consistency Training Improves LLM Agent Robustness Introduces a self-supervised consistency loss across varied tool interfaces to make language model agents robust against notation and naming changes. Preprint	LLMs for code via arxiv · 15 Oct, 15:06	Not relevant Does not focus on software engineering or code generation.
Player-1: Learning to Play from Synthetic Experience Develops a post-training framework that trains computer-use agents for video games using synthetic interactive experiences and an expanded action space. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Proposes a training framework and environment, not an LLM evaluation benchmark.
Player-1: Learning to Play from Synthetic Experience Develops a post-training framework that trains computer-use agents for video games using synthetic interactive experiences and an expanded action space. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on digital game control, not industrial vision or manufacturing inspection.
Player-1: Learning to Play from Synthetic Experience Develops a post-training framework that trains computer-use agents for video games using synthetic interactive experiences and an expanded action space. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on game agent reinforcement learning, not AI safety or guardrails.
Continuum Attention Replaces discrete attention lookup in transformers with integration over a continuous memory curve to improve validation likelihood. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Proposes a continuous attention operator without focusing on efficiency or compression.
Continuum Attention Replaces discrete attention lookup in transformers with integration over a continuous memory curve to improve validation likelihood. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Proposes a novel attention operator, not multi-step autonomous agents.
Continuum Attention Replaces discrete attention lookup in transformers with integration over a continuous memory curve to improve validation likelihood. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on core attention layer math, not AI safety or guardrails.
Continuum Attention Replaces discrete attention lookup in transformers with integration over a continuous memory curve to improve validation likelihood. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Introduces a continuous attention mechanism, not an LLM evaluation framework.
Price of Anarchy of First-Price Auctions in Agentic Markets Analyzes the price of anarchy and economic efficiency of first-price auctions where AI agents bid to serve user prompts. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on auction game theory rather than AI deployment safety risks.
Price of Anarchy of First-Price Auctions in Agentic Markets Analyzes the price of anarchy and economic efficiency of first-price auctions where AI agents bid to serve user prompts. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Theoretical analysis of agent auctions, not an empirical LLM benchmark.
Price of Anarchy of First-Price Auctions in Agentic Markets Analyzes the price of anarchy and economic efficiency of first-price auctions where AI agents bid to serve user prompts. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Analyzes auction economics rather than model compression or efficient inference.
Your Transformer Is Secretly Elastic Presents a retraining-free method to adapt transformer sizes dynamically across diverse computational budgets using joint soft pruning of components. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Focuses on dynamic model pruning, not an LLM benchmark.
Your Transformer Is Secretly Elastic Presents a retraining-free method to adapt transformer sizes dynamically across diverse computational budgets using joint soft pruning of components. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Proposes a transformer pruning technique, not multi-step agent systems.
Your Transformer Is Secretly Elastic Presents a retraining-free method to adapt transformer sizes dynamically across diverse computational budgets using joint soft pruning of components. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on dynamic neural pruning, not AI safety or guardrails.
Co-Evolving Acting and Forecasting for Language Agents Introduces multi-step action forecasting targets alongside actor rollouts to train language agents more effectively from intermediate trajectory steps. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Proposes an agent training method rather than an evaluation benchmark.
Co-Evolving Acting and Forecasting for Language Agents Introduces multi-step action forecasting targets alongside actor rollouts to train language agents more effectively from intermediate trajectory steps. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Focuses on reinforcement learning efficiency, not small models or compression.
Co-Evolving Acting and Forecasting for Language Agents Introduces multi-step action forecasting targets alongside actor rollouts to train language agents more effectively from intermediate trajectory steps. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on agent policy learning, not AI safety or hallucination prevention.
Hierarchical Residual Policy Learning for Real-World Mobile Manipulation with Sparse Human Guidance Proposes a hierarchical residual policy learning framework to fine-tune mobile robot manipulation policies with decoupled base and arm adjustments. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Focuses on robotic reinforcement learning, not LLM agents or tool use.
Hierarchical Residual Policy Learning for Real-World Mobile Manipulation with Sparse Human Guidance Proposes a hierarchical residual policy learning framework to fine-tune mobile robot manipulation policies with decoupled base and arm adjustments. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Focuses on sample-efficient robotic RL, not LLM quantization or compression.
Hierarchical Residual Policy Learning for Real-World Mobile Manipulation with Sparse Human Guidance Proposes a hierarchical residual policy learning framework to fine-tune mobile robot manipulation policies with decoupled base and arm adjustments. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Addresses mobile robot manipulation, not industrial defect detection or visual quality control.
Hierarchical Residual Policy Learning for Real-World Mobile Manipulation with Sparse Human Guidance Proposes a hierarchical residual policy learning framework to fine-tune mobile robot manipulation policies with decoupled base and arm adjustments. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Pertains to robotics control policies, not AI deployment safety or jailbreaks.
Hierarchical Residual Policy Learning for Real-World Mobile Manipulation with Sparse Human Guidance Proposes a hierarchical residual policy learning framework to fine-tune mobile robot manipulation policies with decoupled base and arm adjustments. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Presents a policy fine-tuning algorithm, not an LLM benchmark or evaluation.
Modeling and Understanding Neural Weights of Humanoid Policies with Diffusion Generatively models humanoid robot control policy weights using a latent diffusion framework combined with a linear autoencoder and Diffusion Transformer. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant About humanoid robot control policies, not LLM safety or guardrails.
Modeling and Understanding Neural Weights of Humanoid Policies with Diffusion Generatively models humanoid robot control policy weights using a latent diffusion framework combined with a linear autoencoder and Diffusion Transformer. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Generates policy weights using diffusion, not model compression or efficient serving.
Modeling and Understanding Neural Weights of Humanoid Policies with Diffusion Generatively models humanoid robot control policy weights using a latent diffusion framework combined with a linear autoencoder and Diffusion Transformer. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on humanoid locomotion policies, not industrial defect inspection.
Modeling and Understanding Neural Weights of Humanoid Policies with Diffusion Generatively models humanoid robot control policy weights using a latent diffusion framework combined with a linear autoencoder and Diffusion Transformer. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Focuses on humanoid robotics policy weights, not LLM-based planning agents.
Modeling and Understanding Neural Weights of Humanoid Policies with Diffusion Generatively models humanoid robot control policy weights using a latent diffusion framework combined with a linear autoencoder and Diffusion Transformer. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Studies generative modeling of robot policy weights, not LLM benchmarks.
Laterally Coupled DFB Lasers With Self-Aligned Metal Surface Grating by Holographic Lithography This paper reports the fabrication and continuous-wave optical performance of laterally coupled distributed feedback semiconductor lasers. Peer-reviewedOlder paper (2008) Older paper (2008) — discussed this week	AI safety and reliability in deployment via ieee · 15 Oct, 06:19	Not relevant Semiconductor laser physics paper, completely unrelated to AI safety.
Buffer-Free HEMT With Ultra-Thin AlN Back Barrier and GaN Channel Suppressing Drain Lag and Quiescent Drain Current Drift This paper evaluates a buffer-free transistor structure designed to suppress current drift and lag in high-power electronics. Peer-reviewedOlder paper (2026) Older paper (2026) — discussed this week	AI safety and reliability in deployment via ieee · 15 Oct, 06:19	Not relevant Hardware semiconductor engineering paper, completely unrelated to AI safety.
Reliability study of AlGaN/GaN/Si HEMTs using Capacitance-Voltage measurements This paper surveys capacitance-voltage measurement techniques to evaluate defect states and reliability in gallium nitride transistor devices. Peer-reviewedOlder paper (2025) Older paper (2025) — discussed this week	AI safety and reliability in deployment via ieee · 15 Oct, 06:19	Not relevant About semiconductor transistor reliability, not AI system safety or reliability.

8,101–8,160 of 17,313← Previous Next →