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
D-World: An Explicit World-Language-Action Model with Recursive Self-Improvement under Dual Control Designs an explicit digital-twin world model where robotic agents inspect, simulate, and calibrate physical parameters before acting. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:17	Not relevant Focuses on embodied robotic control, not industrial inspection or defect detection.
D-World: An Explicit World-Language-Action Model with Recursive Self-Improvement under Dual Control Designs an explicit digital-twin world model where robotic agents inspect, simulate, and calibrate physical parameters before acting. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Proposes a model framework rather than evaluating benchmarks or testing methodologies.
D-World: An Explicit World-Language-Action Model with Recursive Self-Improvement under Dual Control Designs an explicit digital-twin world model where robotic agents inspect, simulate, and calibrate physical parameters before acting. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Focuses on robotics and control rather than AI safety guardrails or hallucination.
When LLM Agents See a Conflict but Still Proceed: Cross-Domain Dependencies in Network Slicing Shows that language agents often ignore identified cross-domain dependencies, causing unintended disruptive actions in network management. Preprint	Multimodal models via arxiv · 15 Oct, 06:17	Not relevant Examines text-based network management intents, not multimodal models.
When LLM Agents See a Conflict but Still Proceed: Cross-Domain Dependencies in Network Slicing Shows that language agents often ignore identified cross-domain dependencies, causing unintended disruptive actions in network management. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:17	Not relevant Evaluates agent action execution, not retrieval-augmented generation systems.
When LLM Agents See a Conflict but Still Proceed: Cross-Domain Dependencies in Network Slicing Shows that language agents often ignore identified cross-domain dependencies, causing unintended disruptive actions in network management. Preprint	LLMs for code via arxiv · 15 Oct, 06:17	Not relevant Focuses on network intent operations, not code generation assistants.
When LLM Agents See a Conflict but Still Proceed: Cross-Domain Dependencies in Network Slicing Shows that language agents often ignore identified cross-domain dependencies, causing unintended disruptive actions in network management. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Focuses on agent decision reliability, not efficient inference techniques.
D2: High-Capability Full-Duplex Spoken Language Models from Half-Duplex Backbones Converts half-duplex speech models into streaming full-duplex conversational models capable of simultaneous listening and speaking. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Covers spoken turn-taking mechanics, not deployment safety guardrails.
D2: High-Capability Full-Duplex Spoken Language Models from Half-Duplex Backbones Converts half-duplex speech models into streaming full-duplex conversational models capable of simultaneous listening and speaking. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:17	Not relevant Spoken interaction modeling, not retrieval-augmented generation.
D2: High-Capability Full-Duplex Spoken Language Models from Half-Duplex Backbones Converts half-duplex speech models into streaming full-duplex conversational models capable of simultaneous listening and speaking. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Addresses full-duplex conversion, not model pruning or quantization.
D2: High-Capability Full-Duplex Spoken Language Models from Half-Duplex Backbones Converts half-duplex speech models into streaming full-duplex conversational models capable of simultaneous listening and speaking. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Focuses on duplex speech modeling, not multi-step agent planning.
D2: High-Capability Full-Duplex Spoken Language Models from Half-Duplex Backbones Converts half-duplex speech models into streaming full-duplex conversational models capable of simultaneous listening and speaking. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Model conversion method, not an evaluation benchmark or audit.
D2: High-Capability Full-Duplex Spoken Language Models from Half-Duplex Backbones Converts half-duplex speech models into streaming full-duplex conversational models capable of simultaneous listening and speaking. Preprint	LLMs for code via arxiv · 15 Oct, 06:17	Not relevant Spoken dialogue modeling, not code generation or program repair.
Who is the 'I' in AI? Establishing Decentralized Identity and Accountability for Autonomous Agents Proposes a decentralized identity framework using self-sovereign identity principles to establish verification and accountability for autonomous agents. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Identity specification proposal, not an evaluation benchmark.
EvoQuantLab: Training-Free Dual-Loop Evolution for Auditable Quantitative Research Combines genetic programming and diagnostic evaluation loops to discover quantitative financial trading factors without backtest overfitting. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Proposes a factor discovery system, not an LLM benchmark.
EvoQuantLab: Training-Free Dual-Loop Evolution for Auditable Quantitative Research Combines genetic programming and diagnostic evaluation loops to discover quantitative financial trading factors without backtest overfitting. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Financial factor mining methodology, not AI deployment safety.
SonicWorld: Source-Centric Latent Dynamics for Spatial Audio Reasoning Introduces a dynamic spatial audio reasoning benchmark and an architecture tracking acoustic sources across moving indoor scenes. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Studies spatial audio reasoning models, not autonomous LLM agents.
SonicWorld: Source-Centric Latent Dynamics for Spatial Audio Reasoning Introduces a dynamic spatial audio reasoning benchmark and an architecture tracking acoustic sources across moving indoor scenes. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Focuses on spatial audio understanding, not safety guardrails.
The Format is the Filter: Scoring Format Fixes What an LLM Judge Can Express Demonstrates that the scoring format chosen for an evaluation model strongly restricts its expressive capacity and ranking reliability. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:17	Not relevant Focuses on judging instruction data, not document retrieval systems.
The Format is the Filter: Scoring Format Fixes What an LLM Judge Can Express Demonstrates that the scoring format chosen for an evaluation model strongly restricts its expressive capacity and ranking reliability. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Studies LLM-as-a-judge scoring formats, not multi-step agent workflows.
The Format is the Filter: Scoring Format Fixes What an LLM Judge Can Express Demonstrates that the scoring format chosen for an evaluation model strongly restricts its expressive capacity and ranking reliability. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Data curation format study, not model compression or efficiency.
The Format is the Filter: Scoring Format Fixes What an LLM Judge Can Express Demonstrates that the scoring format chosen for an evaluation model strongly restricts its expressive capacity and ranking reliability. Preprint	Multimodal models via arxiv · 15 Oct, 06:17	Not relevant Evaluates text scoring formats, not multimodal models.
The Format is the Filter: Scoring Format Fixes What an LLM Judge Can Express Demonstrates that the scoring format chosen for an evaluation model strongly restricts its expressive capacity and ranking reliability. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Studies evaluation formatting artifacts, not deployment guardrails or jailbreaks.
The Format is the Filter: Scoring Format Fixes What an LLM Judge Can Express Demonstrates that the scoring format chosen for an evaluation model strongly restricts its expressive capacity and ranking reliability. Preprint	LLMs for code via arxiv · 15 Oct, 06:17	Not relevant Evaluates general instruction-tuning curation, not coding assistance.
Force-Modulated Dexterity: Unified Compliance for Contact-Rich Manipulation Presents a compliant teleoperation control framework that reduces excessive contact forces during dexterous manipulation data collection. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Covers robot teleoperation compliance, not AI deployment guardrails.
Force-Modulated Dexterity: Unified Compliance for Contact-Rich Manipulation Presents a compliant teleoperation control framework that reduces excessive contact forces during dexterous manipulation data collection. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:17	Not relevant Robotic teleoperation and compliance control, not industrial vision inspection.
Force-Modulated Dexterity: Unified Compliance for Contact-Rich Manipulation Presents a compliant teleoperation control framework that reduces excessive contact forces during dexterous manipulation data collection. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Focuses on teleoperated robotics control, not autonomous LLM agents.
Force-Modulated Dexterity: Unified Compliance for Contact-Rich Manipulation Presents a compliant teleoperation control framework that reduces excessive contact forces during dexterous manipulation data collection. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Proposes a robotic control technique, not LLM evaluation.
Learning Perceptual Geometry of Natural Odor Mixtures from LLM-Derived Descriptors Uses language-model perceptual descriptions of complex chemical mixtures to predict perceived odor similarity from molecular composition. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Uses LLM embeddings for chemical biology, not autonomous agents.
Learning Perceptual Geometry of Natural Odor Mixtures from LLM-Derived Descriptors Uses language-model perceptual descriptions of complex chemical mixtures to predict perceived odor similarity from molecular composition. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:17	Not relevant Focuses on molecular property prediction, not retrieval-augmented generation.
Learning Perceptual Geometry of Natural Odor Mixtures from LLM-Derived Descriptors Uses language-model perceptual descriptions of complex chemical mixtures to predict perceived odor similarity from molecular composition. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Focuses on odor geometry, not AI deployment safety.
Learning Perceptual Geometry of Natural Odor Mixtures from LLM-Derived Descriptors Uses language-model perceptual descriptions of complex chemical mixtures to predict perceived odor similarity from molecular composition. Preprint	LLMs for code via arxiv · 15 Oct, 06:17	Not relevant Application in computational chemistry and olfaction, not code generation.
Learning Perceptual Geometry of Natural Odor Mixtures from LLM-Derived Descriptors Uses language-model perceptual descriptions of complex chemical mixtures to predict perceived odor similarity from molecular composition. Preprint	Multimodal models via arxiv · 15 Oct, 06:17	Not relevant Maps chemical mixtures to sensory space, not vision/speech multimodality.
Learning Perceptual Geometry of Natural Odor Mixtures from LLM-Derived Descriptors Uses language-model perceptual descriptions of complex chemical mixtures to predict perceived odor similarity from molecular composition. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Scientific olfaction study, not efficient serving or model quantization.
Learning Perceptual Geometry of Natural Odor Mixtures from LLM-Derived Descriptors Uses language-model perceptual descriptions of complex chemical mixtures to predict perceived odor similarity from molecular composition. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Study on odor perception representations, not LLM benchmark evaluation.
Generative Flow on Symbolic Abstractions for Embodiment Capability Discovery Discovers robot capabilities using a generative flow network that creates symbolic task skeletons grounded in physical robot affordances. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:17	Not relevant General robot manipulation discovery, not industrial defect detection.
Generative Flow on Symbolic Abstractions for Embodiment Capability Discovery Discovers robot capabilities using a generative flow network that creates symbolic task skeletons grounded in physical robot affordances. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Robotics curriculum discovery using GFlowNets, not language agent systems.
Generative Flow on Symbolic Abstractions for Embodiment Capability Discovery Discovers robot capabilities using a generative flow network that creates symbolic task skeletons grounded in physical robot affordances. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Focuses on robotic skill acquisition, not model compression.
Generative Flow on Symbolic Abstractions for Embodiment Capability Discovery Discovers robot capabilities using a generative flow network that creates symbolic task skeletons grounded in physical robot affordances. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Proposes a task generation framework, not an evaluation benchmark.
Generative Flow on Symbolic Abstractions for Embodiment Capability Discovery Discovers robot capabilities using a generative flow network that creates symbolic task skeletons grounded in physical robot affordances. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Focuses on robot task learning, not AI safety guardrails.
ChemExplain: A Multimodal Benchmark for Explanatory Chemical Reasoning Presents a multimodal benchmark testing whether models can explain observed chemical effects by linking structural features to reaction mechanisms. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:17	Not relevant Focuses on chemistry molecular diagrams, not industrial inspection.
ChemExplain: A Multimodal Benchmark for Explanatory Chemical Reasoning Presents a multimodal benchmark testing whether models can explain observed chemical effects by linking structural features to reaction mechanisms. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Chemistry QA benchmark, not AI safety or jailbreak prevention.
ChemExplain: A Multimodal Benchmark for Explanatory Chemical Reasoning Presents a multimodal benchmark testing whether models can explain observed chemical effects by linking structural features to reaction mechanisms. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Benchmark paper for chemistry reasoning, not autonomous LLM agents.
FreeSolo: Linear-time Sparse Attention with Zero-Shot Length Extrapolation Introduces a native sparse attention mechanism that combines sliding windows and keypoint selection for linear-time context extrapolation. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Focuses on architectural design, not benchmark creation or evaluation.
FreeSolo: Linear-time Sparse Attention with Zero-Shot Length Extrapolation Introduces a native sparse attention mechanism that combines sliding windows and keypoint selection for linear-time context extrapolation. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Proposes a sparse attention mechanism, not agent architectures.
FreeSolo: Linear-time Sparse Attention with Zero-Shot Length Extrapolation Introduces a native sparse attention mechanism that combines sliding windows and keypoint selection for linear-time context extrapolation. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Focuses on attention length extrapolation, not deployment safety.
Size Generalization for Diffusion Routing Solvers Uses reinforcement learning on large routing instances to help diffusion-based solvers generalize beyond their training instance sizes. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Covers combinatorial optimization algorithms, not LLM evaluation.
Size Generalization for Diffusion Routing Solvers Uses reinforcement learning on large routing instances to help diffusion-based solvers generalize beyond their training instance sizes. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Addresses diffusion combinatorial optimization solvers, not LLM agents.
Size Generalization for Diffusion Routing Solvers Uses reinforcement learning on large routing instances to help diffusion-based solvers generalize beyond their training instance sizes. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Focuses on TSP/CVRP routing solvers, not AI safety.
Deleting Code Without Losing Knowledge: Regenerative Software for Python Libraries Applies regenerative software primitives so programs can be deleted and rebuilt by agents without losing architectural intent and knowledge. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Focuses on software architecture patterns, not AI safety guardrails.
Deleting Code Without Losing Knowledge: Regenerative Software for Python Libraries Applies regenerative software primitives so programs can be deleted and rebuilt by agents without losing architectural intent and knowledge. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Describes a software engineering methodology, not benchmark evaluation.
Releasing the Inner Jev: A Simple Recipe for Open Decision Models The paper demonstrates recipes to extract single-pass probability decisions directly from open instruction-tuned language models. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Studies single-forward-pass decision heads, not multi-step agent planning.
Releasing the Inner Jev: A Simple Recipe for Open Decision Models The paper demonstrates recipes to extract single-pass probability decisions directly from open instruction-tuned language models. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Covers logit classification and capability metrics, not deployment guardrails.
AutoMARS: Automatic and Scalable Multi-Agent Large Language Model Framework for Supply Chain Risk Assessment The paper proposes a multi-agent framework to coordinate analytical tools and evaluate multi-factor supply chain risks across diverse locations. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Focuses on multi-agent application design, not benchmark development.
AutoMARS: Automatic and Scalable Multi-Agent Large Language Model Framework for Supply Chain Risk Assessment The paper proposes a multi-agent framework to coordinate analytical tools and evaluate multi-factor supply chain risks across diverse locations. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Domain risk assessment tool, not AI safety and reliability.
Compute-optimal data scaling for neural surrogates via multi-fidelity training The paper demonstrates multi-fidelity training to optimize data generation compute and error scaling for neural PDE surrogates. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Focuses on numerical PDE simulation accuracy, not AI safety.
Compute-optimal data scaling for neural surrogates via multi-fidelity training The paper demonstrates multi-fidelity training to optimize data generation compute and error scaling for neural PDE surrogates. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Covers scientific simulator scaling, not LLM evaluation benchmarks.
Compute-optimal data scaling for neural surrogates via multi-fidelity training The paper demonstrates multi-fidelity training to optimize data generation compute and error scaling for neural PDE surrogates. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Studies surrogate models for PDEs, not LLM agents.
IsoVRBench: Video Reward Modeling Without Human Feedback The paper presents a benchmark of synthetic paired comparisons to evaluate video reward models across specific visual and motion dimensions. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:17	Not relevant Studies generative video reward modeling, not industrial defect detection.
IsoVRBench: Video Reward Modeling Without Human Feedback The paper presents a benchmark of synthetic paired comparisons to evaluate video reward models across specific visual and motion dimensions. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Focuses on video reward models, not autonomous planning agents.

9,721–9,780 of 13,754← Previous Next →