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
What Happens to the Goal? Distinct Failures of Policy Alignment in Goal Misgeneralization This paper analyzes three distinct failure modes where reinforcement learning agents misgeneralize goals despite competent behavior. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Evaluates RL toy tasks, not industrial visual inspection.
Exact Cut Complexity of Equal-Length Proportional Cake Cutting This paper establishes the exact cut complexity required for equal-length proportional cake cutting among multiple agents. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Theoretical cut complexity analysis, not an LLM benchmark.
Exact Cut Complexity of Equal-Length Proportional Cake Cutting This paper establishes the exact cut complexity required for equal-length proportional cake cutting among multiple agents. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Mathematical algorithmic game theory, not LLM-based autonomous agents.
Exact Cut Complexity of Equal-Length Proportional Cake Cutting This paper establishes the exact cut complexity required for equal-length proportional cake cutting among multiple agents. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Purely theoretical mathematics, not AI deployment safety.
ProtModernBERT: Compute-Efficient Protein Language Modeling This paper introduces an efficient encoder-only protein language model incorporating modern architectural updates to lower training costs. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Focuses on protein language modeling, not tool-using agents.
ProtModernBERT: Compute-Efficient Protein Language Modeling This paper introduces an efficient encoder-only protein language model incorporating modern architectural updates to lower training costs. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on biological sequence modeling, not deployment safety.
ProtModernBERT: Compute-Efficient Protein Language Modeling This paper introduces an efficient encoder-only protein language model incorporating modern architectural updates to lower training costs. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Evaluates a specific model, does not propose new benchmarks.
Does the Linguistic Register of Thinking Matter? Wenyan as a Compact Reasoning Register for Chinese LLMs This paper investigates using Classical Chinese as a compact intermediate reasoning register to reduce token length in Chinese language models. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on token efficiency, not safety or guardrails.
Does the Linguistic Register of Thinking Matter? Wenyan as a Compact Reasoning Register for Chinese LLMs This paper investigates using Classical Chinese as a compact intermediate reasoning register to reduce token length in Chinese language models. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Investigates linguistic registers for reasoning, not tool-using agents.
Does the Linguistic Register of Thinking Matter? Wenyan as a Compact Reasoning Register for Chinese LLMs This paper investigates using Classical Chinese as a compact intermediate reasoning register to reduce token length in Chinese language models. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Exclusively text-based language model reasoning.
Does the Linguistic Register of Thinking Matter? Wenyan as a Compact Reasoning Register for Chinese LLMs This paper investigates using Classical Chinese as a compact intermediate reasoning register to reduce token length in Chinese language models. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Uses existing benchmarks, does not propose evaluation methods.
Does the Linguistic Register of Thinking Matter? Wenyan as a Compact Reasoning Register for Chinese LLMs This paper investigates using Classical Chinese as a compact intermediate reasoning register to reduce token length in Chinese language models. Preprint	LLMs for code via arxiv · 15 Oct, 15:06	Not relevant Focuses on natural language reasoning, not code generation.
Does the Linguistic Register of Thinking Matter? Wenyan as a Compact Reasoning Register for Chinese LLMs This paper investigates using Classical Chinese as a compact intermediate reasoning register to reduce token length in Chinese language models. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 15:06	Not relevant Does not involve external retrieval or document grounding.
PRISMATIC : Prescription Risk Inspection System for Multi-Agent Treatment Interaction in Clinical Decision-Making This paper proposes a multi-agent system designed to reduce clinical medication errors through dynamic collaborative coordination. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Processes clinical text records, not multimodal data.
PRISMATIC : Prescription Risk Inspection System for Multi-Agent Treatment Interaction in Clinical Decision-Making This paper proposes a multi-agent system designed to reduce clinical medication errors through dynamic collaborative coordination. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Not about model pruning, distillation, or serving efficiency.
PRISMATIC : Prescription Risk Inspection System for Multi-Agent Treatment Interaction in Clinical Decision-Making This paper proposes a multi-agent system designed to reduce clinical medication errors through dynamic collaborative coordination. Preprint	LLMs for code via arxiv · 15 Oct, 15:06	Not relevant Applies to medical prescription workflows, not software code generation.
PRISMATIC : Prescription Risk Inspection System for Multi-Agent Treatment Interaction in Clinical Decision-Making This paper proposes a multi-agent system designed to reduce clinical medication errors through dynamic collaborative coordination. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Presents a multi-agent framework, not general LLM benchmarking.
PRISMATIC : Prescription Risk Inspection System for Multi-Agent Treatment Interaction in Clinical Decision-Making This paper proposes a multi-agent system designed to reduce clinical medication errors through dynamic collaborative coordination. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 15:06	Not relevant Does not focus on information retrieval or RAG architectures.
LabOPBench: A Multimodal Benchmark for Evidence-Grounded Laboratory Decision Making This paper introduces a multimodal benchmark evaluating AI models on evidence-grounded decision making in chemistry and materials laboratories. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Introduces an evaluation benchmark, not an autonomous agent system.
LabOPBench: A Multimodal Benchmark for Evidence-Grounded Laboratory Decision Making This paper introduces a multimodal benchmark evaluating AI models on evidence-grounded decision making in chemistry and materials laboratories. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Benchmarking scientific reasoning, not deployment safety or guardrails.
LiFi: LiDAR Generation from Multi-View Images via Geometric and Semantic Collaborative Guidance This paper presents a dual-branch latent diffusion method to generate LiDAR point clouds from multi-view camera images. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on sensory data synthesis, not deployment safety.
LiFi: LiDAR Generation from Multi-View Images via Geometric and Semantic Collaborative Guidance This paper presents a dual-branch latent diffusion method to generate LiDAR point clouds from multi-view camera images. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on synthetic LiDAR from images, not industrial inspection.
LiFi: LiDAR Generation from Multi-View Images via Geometric and Semantic Collaborative Guidance This paper presents a dual-branch latent diffusion method to generate LiDAR point clouds from multi-view camera images. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Covers LiDAR point cloud generation, not language model agents.
LiFi: LiDAR Generation from Multi-View Images via Geometric and Semantic Collaborative Guidance This paper presents a dual-branch latent diffusion method to generate LiDAR point clouds from multi-view camera images. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Presents a generative 3D model, not an evaluation benchmark.
One Agent per Zone: Decentralised Active Inference under Partial Observability for Multi-Zone HVAC Control on Edge Hardware This paper presents a decentralized active inference controller for multi-zone building heating and cooling systems on edge hardware. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Presents an HVAC control system, not an evaluation benchmark.
One Agent per Zone: Decentralised Active Inference under Partial Observability for Multi-Zone HVAC Control on Edge Hardware This paper presents a decentralized active inference controller for multi-zone building heating and cooling systems on edge hardware. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Traditional active-inference control for HVAC, not language model agents.
One Agent per Zone: Decentralised Active Inference under Partial Observability for Multi-Zone HVAC Control on Edge Hardware This paper presents a decentralized active inference controller for multi-zone building heating and cooling systems on edge hardware. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on building energy optimization, not AI safety guardrails.
StateCraft: Augmenting Video World Models with Abstract-State Reasoning This paper pairs language models with video diffusion to maintain persistent abstract states across dynamic video world interactions. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Does not address model compression or serving efficiency.
StateCraft: Augmenting Video World Models with Abstract-State Reasoning This paper pairs language models with video diffusion to maintain persistent abstract states across dynamic video world interactions. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Concerns generative video interfaces, not industrial visual inspection.
StateCraft: Augmenting Video World Models with Abstract-State Reasoning This paper pairs language models with video diffusion to maintain persistent abstract states across dynamic video world interactions. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Does not study model safety, robustness, or reliability guardrails.
StateCraft: Augmenting Video World Models with Abstract-State Reasoning This paper pairs language models with video diffusion to maintain persistent abstract states across dynamic video world interactions. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Focuses on video world generation, not multi-step agent planning.
StateCraft: Augmenting Video World Models with Abstract-State Reasoning This paper pairs language models with video diffusion to maintain persistent abstract states across dynamic video world interactions. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Introduces an architecture for video synthesis, not benchmarking methodology.
Learning Perception to Action Rules through Reinforcement Learning for Theory-of-Mind Reasoning This paper trains language models using reinforcement learning to generate explicit perception-to-action rules for theory-of-mind reasoning tasks. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 15:06	Not relevant Does not involve external retrieval or knowledge grounding.
Learning Perception to Action Rules through Reinforcement Learning for Theory-of-Mind Reasoning This paper trains language models using reinforcement learning to generate explicit perception-to-action rules for theory-of-mind reasoning tasks. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Focuses on Theory-of-Mind reasoning in LLMs, not autonomous agents.
Learning Perception to Action Rules through Reinforcement Learning for Theory-of-Mind Reasoning This paper trains language models using reinforcement learning to generate explicit perception-to-action rules for theory-of-mind reasoning tasks. Preprint	LLMs for code via arxiv · 15 Oct, 15:06	Not relevant Does not address coding assistants or program synthesis.
Learning Perception to Action Rules through Reinforcement Learning for Theory-of-Mind Reasoning This paper trains language models using reinforcement learning to generate explicit perception-to-action rules for theory-of-mind reasoning tasks. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Purely text-based reasoning without vision or multimodal components.
Learning Perception to Action Rules through Reinforcement Learning for Theory-of-Mind Reasoning This paper trains language models using reinforcement learning to generate explicit perception-to-action rules for theory-of-mind reasoning tasks. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Uses benchmarks for experiments, does not propose evaluation methods.
Learning Perception to Action Rules through Reinforcement Learning for Theory-of-Mind Reasoning This paper trains language models using reinforcement learning to generate explicit perception-to-action rules for theory-of-mind reasoning tasks. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Not focused on model compression, distillation, or efficient inference.
Learning Perception to Action Rules through Reinforcement Learning for Theory-of-Mind Reasoning This paper trains language models using reinforcement learning to generate explicit perception-to-action rules for theory-of-mind reasoning tasks. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Covers cognitive reasoning in LLMs, not safety or guardrails.
ReproBAIT: Can coding agents build their own biological AI tools? This paper introduces a benchmark evaluating whether coding agents can reimplement and train biological AI tools from published scientific papers. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Evaluates tool reproduction capabilities, not model compression or efficiency.
ReproBAIT: Can coding agents build their own biological AI tools? This paper introduces a benchmark evaluating whether coding agents can reimplement and train biological AI tools from published scientific papers. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Does not focus on safety guardrails or deployment risks.
VaryST: Generalizable Spatio-Temporal Forecasting Beyond the Closed-World Setting This paper presents a compact spatio-temporal forecasting model designed to generalize across shifting spatial domains and varying observation availability. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Compact forecasting model, not language model compression or serving.
VaryST: Generalizable Spatio-Temporal Forecasting Beyond the Closed-World Setting This paper presents a compact spatio-temporal forecasting model designed to generalize across shifting spatial domains and varying observation availability. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Focuses on spatio-temporal forecasting, not autonomous planning agents.
VaryST: Generalizable Spatio-Temporal Forecasting Beyond the Closed-World Setting This paper presents a compact spatio-temporal forecasting model designed to generalize across shifting spatial domains and varying observation availability. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Presents a forecasting model architecture, not evaluation methodology.
VaryST: Generalizable Spatio-Temporal Forecasting Beyond the Closed-World Setting This paper presents a compact spatio-temporal forecasting model designed to generalize across shifting spatial domains and varying observation availability. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Does not address AI safety, jailbreaks, or deployment guardrails.
One Monitor Does Not Fit All: Formalism-Agnostic Runtime Verification for Agentic AI This paper develops a runtime verification architecture that decouples monitoring formalisms from execution boundaries to safely control AI agents. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Presents a runtime monitoring architecture, not an LLM benchmark.
ActionOPD: Distilling Decisions, Not Tokens This paper proposes an on-policy distillation method that aligns student agents using semantic actions rather than token-level supervision. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Addresses policy imitation for agents, not safety or guardrails.
ActionOPD: Distilling Decisions, Not Tokens This paper proposes an on-policy distillation method that aligns student agents using semantic actions rather than token-level supervision. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Introduces a training distillation method, not an evaluation framework.
Teaching Agents in their Own Style: Blackbox Teacher Distillation for Web Agents This paper presents a distillation method where a teacher model minimally edits a student web agent's reasoning traces at failure points. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Deals with agent distillation efficiency, not safety or guardrails.
Teaching Agents in their Own Style: Blackbox Teacher Distillation for Web Agents This paper presents a distillation method where a teacher model minimally edits a student web agent's reasoning traces at failure points. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Focus is distillation methodology, not evaluation benchmark design.
LAGO: Language Agents with Reusable Growing Options This paper introduces an architecture that stores and reuses specialized language agents as temporally extended options for complex coding tasks. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Addresses agent task performance rather than safety guardrails or red-teaming.
LAGO: Language Agents with Reusable Growing Options This paper introduces an architecture that stores and reuses specialized language agents as temporally extended options for complex coding tasks. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Focuses on an agent framework evaluated on existing benchmarks, not new evaluation methods.
Memory-Efficient Subspace Optimization with Residual Correction: From Momentum SGD to Muon This paper presents a memory-efficient subspace optimization framework using residual correction to stabilize language model training. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Investigates optimization algorithms for neural network training, not AI agents.
Memory-Efficient Subspace Optimization with Residual Correction: From Momentum SGD to Muon This paper presents a memory-efficient subspace optimization framework using residual correction to stabilize language model training. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Develops training optimizers, not model evaluation frameworks.
Memory-Efficient Subspace Optimization with Residual Correction: From Momentum SGD to Muon This paper presents a memory-efficient subspace optimization framework using residual correction to stabilize language model training. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Does not examine AI safety, alignment, or deployment guardrails.
DeltaStreamer: Towards Human-Like Agentic Streaming Video Understanding This paper proposes an agentic video framework combining change-aware memory and targeted replay for streaming video understanding. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on video reasoning capabilities rather than safety risks or guardrails.
DeltaStreamer: Towards Human-Like Agentic Streaming Video Understanding This paper proposes an agentic video framework combining change-aware memory and targeted replay for streaming video understanding. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Studies streaming video comprehension rather than manufacturing defect detection.
DeltaStreamer: Towards Human-Like Agentic Streaming Video Understanding This paper proposes an agentic video framework combining change-aware memory and targeted replay for streaming video understanding. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Proposes a streaming video method, not an evaluation benchmark.
Lost in the Fallback: How Reliably Do Typed Decision Models Use Fallback Options? This paper evaluates how reliably typed decision models switch to fallback options and remain consistent under equivalent decision rules. Preprint	AI agents via arxiv · 15 Oct, 15:06	Not relevant Studies typed classification models and routing rules, not agent tool execution.
Euler: Towards Human-Centered Multi-Agent Mathematical Discovery This paper introduces a multi-agent mathematical discovery system that organizes proofs, assumptions, and failed attempts into structured research graphs. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Presents a multi-agent mathematical framework rather than a general evaluation benchmark.

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