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
AutoBio+: Benchmarking Dexterous Manipulation with Dynamic Experimental Phenomena in Realistic Laboratories Introduces a simulation benchmark evaluating robotic dexterous manipulation in wet-lab environments under dynamic visual phenomena like vapor and flames. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:29	Not relevant A benchmark for laboratory dexterous robot manipulation rather than industrial computer vision inspection or defect detection.
Towards a Unified Taxonomy of Agricultural Harvesting Technologies: Linking Physical Interaction, Automation, and Selectivity Proposes a unified taxonomy classifying agricultural harvesting technologies across physical interaction mechanisms and levels of automation. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:29	Not relevant Proposes a broad taxonomy of agricultural harvesting technologies, not computer vision models for industrial inspection.
When LiDAR Fades, Radar Takes Over: LiDAR Reliability-Aware Adaptive Localization Under Airborne Obscurants Detects LiDAR degradation in degraded visual environments using an LSTM autoencoder to adaptively transfer odometry weight to radar sensors. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:29	Not relevant Focuses on multi-sensor radar/LiDAR odometry in subterranean tunnels rather than industrial visual inspection.
Mapless, Stabilizing, and Anti-Stuck Flipper Control for Articulated Tracked Robots Proposes a mapless, drift-free flipper controller for tracked robots using short-window motion cues and IMU stabilization. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:29	Not relevant Presents flipper control algorithms using IMU and motion cues, without industrial computer vision components.
HorizonNav: Geometry-Guided Video Diffusion for Anticipatory 3D Robot Navigation Generates anticipatory 3D robot navigation representations from single RGB images using text-prompted video diffusion and geometric depth alignment. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:29	Not relevant Focuses on anticipatory 3D robot navigation with video diffusion, not industrial vision applications.
BT-Agent: Deploying Onboard Robot Agents with Behavior Trees and Multi-Fidelity Evaluation Combines language-model task planning with onboard behavior-tree skill execution and multi-fidelity benchmarking for quadruped robot deployments. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:29	Not relevant Covers onboard mobile robot agent architectures with behavior trees, not industrial computer vision inspection.
Noise Space Learning for VLA Adaptation Adapts pretrained vision-language-action models by learning context-conditioned noise distributions while freezing the underlying base policy. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:29	Not relevant Addresses vision-language-action policy adaptation for general robotics manipulation, not computer vision for industrial applications.
Quantitative Verification of Infinite-State Networks Presents a formal verification framework for quantitative properties of recursive infinite-state networks using pumping semirings. Preprint	LLMs for code via arxiv · 12 Oct, 16:29	Not relevant Focuses on formal quantitative verification of infinite-state networks, not language models for code.
VortexSynth: Profile-guided benchmark reconstruction for GPU architecture research Automates GPU benchmark reconstruction by profiling reference workloads and synthesizing equivalent target-architecture kernel implementations. Preprint	LLMs for code via arxiv · 12 Oct, 16:29	Not relevant Deals with GPU benchmark reconstruction and architecture profiling rather than language models for software engineering.
Coexponential Exploration in the Clef Programming Language Develops a coexponential semantic model for concurrent services in the Clef language using delimited continuations to verify state ownership. Preprint	LLMs for code via arxiv · 12 Oct, 16:29	Not relevant Focuses on programming language design and formal verification, not on language models for code.
A Simplified Layout Algebra for GPU Kernels Formulates a simplified layout algebra for GPU kernels by explicitly typing coordinate spaces to eliminate complex admissibility checks. Preprint	LLMs for code via arxiv · 12 Oct, 16:29	Not relevant Presents formal programming language layout algebra for GPU kernels, not LLMs for code or software engineering.
DIA: A Deep Reinforcement Learning-Based Interest-Aware ABR Scheme for Cloud Gaming Presents a deep reinforcement learning adaptive bitrate scheme for cloud gaming that prioritizes perceptual object quality using semantic segmentation. Peer-reviewed	Multimodal models via arxiv · 12 Oct, 16:29	Not relevant Focuses on adaptive video streaming bitrate in cloud gaming, not multimodal language-vision foundation models.
ConventionPlay: Capability-Limited Training for Robust Ad-Hoc Collaboration Introduces a reinforcement learning method where agents learn ad-hoc collaboration by training against partners with varied convention adaptability. Preprint	AI agents via arxiv · 12 Oct, 16:29	Not relevant Studies classical reinforcement learning for ad-hoc teamwork conventions, not LLM agents.
Policy Synthesis for Finite Populations of MDP Agents under Aggregate Reach-Avoid Chance Constraints Synthesizes control policies for finite MDP agent populations under aggregate reach-avoid chance constraints using moment propagation and Cantelli inequalities. Preprint	AI agents via arxiv · 12 Oct, 16:29	Not relevant Covers mathematical density control and Markov decision processes, not LLM agents.
SoftwareGym: Scaling Computer-Use Agent Training with Diverse Synthesized Software Environments Introduces an automated environment generation pipeline to synthesize diverse runnable desktop GUI software applications for training computer-use agents. Preprint	AI safety and reliability in deployment via arxiv · 12 Oct, 16:29	Not relevant Centers on environment generation and agent benchmark training, not deployment safety or guardrails.
SoftwareGym: Scaling Computer-Use Agent Training with Diverse Synthesized Software Environments Introduces an automated environment generation pipeline to synthesize diverse runnable desktop GUI software applications for training computer-use agents. Preprint	LLMs for code via arxiv · 12 Oct, 16:29	Not relevant Focuses on generating environments for computer-use agents, not models that write, review, or fix code.
Distributed Harmonic-Covariance Feedback for Hole Closure in Planar Robot Swarms Proposes distributed harmonic-covariance feedback using Hodge Laplacians for hole closure in planar multi-agent robot swarms. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:29	Not relevant Presents mathematical feedback laws for geometric coverage, not industrial computer vision.
Distributed Harmonic-Covariance Feedback for Hole Closure in Planar Robot Swarms Proposes distributed harmonic-covariance feedback using Hodge Laplacians for hole closure in planar multi-agent robot swarms. Preprint	AI agents via arxiv · 12 Oct, 16:29	Not relevant Covers distributed control theory and algebraic topology for robot swarms, not LLM agents.
Robust and Scalable UAV-UGV Planning for Aerial Monitoring under Energy and Precedence Constraints Formulates a robust trajectory and timing planner for coordinated UAV-UGV aerial monitoring teams under energy and precedence constraints. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:29	Not relevant Addresses routing and scheduling algorithms for vehicles, not industrial computer vision.
Robust and Scalable UAV-UGV Planning for Aerial Monitoring under Energy and Precedence Constraints Formulates a robust trajectory and timing planner for coordinated UAV-UGV aerial monitoring teams under energy and precedence constraints. Preprint	AI agents via arxiv · 12 Oct, 16:29	Not relevant Focuses on combinatorial trajectory planning for UAV-UGV vehicles, not LLM agent systems.
Failure-Resilient Multi-Robot Coordination with $k$-Connectivity Constrained Submodular Maximization Proposes an algorithm for multi-robot submodular maximization under communication k-connectivity constraints resilient to robot failures. Preprint	AI agents via arxiv · 12 Oct, 16:29	Not relevant Deals with submodular maximization for robot network connectivity, not LLM agents.
Failure-Resilient Multi-Robot Coordination with $k$-Connectivity Constrained Submodular Maximization Proposes an algorithm for multi-robot submodular maximization under communication k-connectivity constraints resilient to robot failures. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:29	Not relevant Covers multi-robot path planning and connectivity resilience, not industrial computer vision.
The value of information and the emergence of communication in evolved e-puck robots Investigates conditions under which communication signals emerge between simulated autonomous robots performing spatial foraging tasks. Preprint	AI agents via arxiv · 12 Oct, 16:29	Not relevant Studies emergent communication via recurrent networks in simulated e-puck robots, not LLM agents.
The value of information and the emergence of communication in evolved e-puck robots Investigates conditions under which communication signals emerge between simulated autonomous robots performing spatial foraging tasks. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:29	Not relevant Focuses on robot navigation and communication, not industrial computer vision or defect inspection.
The Limits of Manipulation within Personalized Incentive Policies Analyzes the theoretical limits of agent manipulation in personalized incentive systems where the regulator learns user profiles over time. Preprint	AI agents via arxiv · 12 Oct, 16:29	Not relevant Analyzes Stackelberg game theory and incentive policies, not LLM agents or tool-use planning.
Limit-sure Winning in Team Games without Shared Randomness Analyzes computational complexity of limit-sure winning objectives for cooperative agent teams lacking shared randomness in stochastic games. Preprint	AI agents via arxiv · 12 Oct, 16:29	Not relevant Theoretical analysis of stochastic game theory and formal verification, not LLM agents.
Cooperative Aerial Transportation of a Payload with a Sliding Cable Attachment Develops trajectory generation and geometric control for dual-quadrotor cooperative transport of payloads with sliding cable attachments. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:29	Not relevant Focuses on aerial transportation dynamics and geometry, not computer vision or industrial visual inspection.
Cooperative Aerial Transportation of a Payload with a Sliding Cable Attachment Develops trajectory generation and geometric control for dual-quadrotor cooperative transport of payloads with sliding cable attachments. Preprint	AI agents via arxiv · 12 Oct, 16:29	Not relevant Covers classical quadrotor dynamics and cable control, not language-model-based agent planning or tool use.
MARGoS: A Configuration-Driven Platform for Reproducible MARL Experiments in ARGoS Introduces a configuration-driven platform for reproducible multi-agent reinforcement learning experiments within the ARGoS swarm robotics simulator. Peer-reviewed	Computer vision for industrial applications via arxiv · 12 Oct, 16:29	Not relevant Examines swarm robotics simulation infrastructure, not computer vision for industrial inspection or manufacturing.
MARGoS: A Configuration-Driven Platform for Reproducible MARL Experiments in ARGoS Introduces a configuration-driven platform for reproducible multi-agent reinforcement learning experiments within the ARGoS swarm robotics simulator. Peer-reviewed	AI safety and reliability in deployment via arxiv · 12 Oct, 16:29	Not relevant Focuses on experimental software artifacts in MARL, not deployed AI safety, guardrails, or alignment.
MARGoS: A Configuration-Driven Platform for Reproducible MARL Experiments in ARGoS Introduces a configuration-driven platform for reproducible multi-agent reinforcement learning experiments within the ARGoS swarm robotics simulator. Peer-reviewed	AI agents via arxiv · 12 Oct, 16:29	Not relevant Addresses reproducibility infrastructure for MARL swarm robotics, not LLM-based agent planning or execution.
MARGoS: A Configuration-Driven Platform for Reproducible MARL Experiments in ARGoS Introduces a configuration-driven platform for reproducible multi-agent reinforcement learning experiments within the ARGoS swarm robotics simulator. Peer-reviewed	LLMs for code via arxiv · 12 Oct, 16:29	Not relevant Focuses on experiment reproducibility pipelines in reinforcement learning, not LLMs for code or software engineering.
What is the goal of unsupervised machine learning? Argues conceptually that unsupervised machine learning serves four distinct goals rather than a single unifying objective. Preprint	AI safety and reliability in deployment via arxiv · 12 Oct, 16:29	Not relevant Does not address safety, hallucination, guardrails, or reliability in deployed AI systems.
What is the goal of unsupervised machine learning? Argues conceptually that unsupervised machine learning serves four distinct goals rather than a single unifying objective. Preprint	Small and efficient models via arxiv · 12 Oct, 16:29	Not relevant Focuses on general machine learning definitions, not small models, quantization, or efficient inference.
What is the goal of unsupervised machine learning? Argues conceptually that unsupervised machine learning serves four distinct goals rather than a single unifying objective. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:29	Not relevant Conceptual position paper on unsupervised learning goals, not about evaluating or benchmarking LLMs.
Does an Illumination Prior Help Face-Swap Detection? A Controlled Study of Temporal Self-Blended Images Evaluates whether temporal illumination inconsistency priors improve face-swap deepfake detection performance across diverse video datasets. Preprint	Small and efficient models via arxiv · 12 Oct, 16:29	Not relevant Investigates face-swap detection data blending, not neural network compression or inference efficiency.
Does an Illumination Prior Help Face-Swap Detection? A Controlled Study of Temporal Self-Blended Images Evaluates whether temporal illumination inconsistency priors improve face-swap deepfake detection performance across diverse video datasets. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:29	Not relevant Evaluates training techniques for face-swap detectors, not language model evaluation or general AI benchmarks.
Addressing Overcommitment in the Reasoning of Gendered Economic Memes under Multimodal Ambiguity Proposes a multimodal reasoning framework to avoid biased role attributions in underspecified or ambiguous social memes. Peer-reviewed	Small and efficient models via arxiv · 12 Oct, 16:29	Not relevant Focuses on multimodal meme reasoning and contextual sufficiency, not model compression or efficiency.
Addressing Overcommitment in the Reasoning of Gendered Economic Memes under Multimodal Ambiguity Proposes a multimodal reasoning framework to avoid biased role attributions in underspecified or ambiguous social memes. Peer-reviewed	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:29	Not relevant Presents a meme reasoning framework and dataset, not a general LLM evaluation methodology or benchmark study.
Spectral Weight Decay: Inducing Low-Rank Structure in Neural Network Weights Introduces a spectral weight decay update inducing low-rank weight matrices to improve SVD-based post-training model compression. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:29	Not relevant Introduces a weight decay regularizer, not an LLM benchmark, leaderboard, or evaluation framework.
Spectral Weight Decay: Inducing Low-Rank Structure in Neural Network Weights Introduces a spectral weight decay update inducing low-rank weight matrices to improve SVD-based post-training model compression. Preprint	AI safety and reliability in deployment via arxiv · 12 Oct, 16:29	Not relevant Focuses on low-rank weight regularization and compression, not deployment safety, guardrails, or alignment.
Correlational Training of Morphological Neural Networks Presents a correlation-based multiplicative weight update method for training morphological neural network layers without standard gradient backpropagation. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:29	Not relevant Presents an alternative update rule for morphological layers, not an evaluation framework or LLM benchmark.
Correlational Training of Morphological Neural Networks Presents a correlation-based multiplicative weight update method for training morphological neural network layers without standard gradient backpropagation. Preprint	AI safety and reliability in deployment via arxiv · 12 Oct, 16:29	Not relevant Focuses on backpropagation alternatives for morphological layers, not AI deployment safety or guardrails.
Correlational Training of Morphological Neural Networks Presents a correlation-based multiplicative weight update method for training morphological neural network layers without standard gradient backpropagation. Preprint	Small and efficient models via arxiv · 12 Oct, 16:29	Not relevant Investigates optimization methods for morphological networks, not model compression, distillation, or quantization.
TraceRelay: Attention-Aligned Recurrence over Rolling Traces Introduces an attention-aligned recurrent architecture that maintains persistent state representations across sequences using rolling low-dimensional traces. Preprint	AI safety and reliability in deployment via arxiv · 12 Oct, 16:29	Not relevant Focuses on architecture design and synthetic sequence length generalization, not deployment safety or guardrails.
TraceRelay: Attention-Aligned Recurrence over Rolling Traces Introduces an attention-aligned recurrent architecture that maintains persistent state representations across sequences using rolling low-dimensional traces. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:29	Not relevant Proposes a recurrent neural architecture, not an evaluation framework or benchmark for language models.
The Ball and the Box: Two Geometries of Computation in Superposition Derives mathematical dimension thresholds required to compute Boolean gates using neural representations stored in superposition. Preprint	AI safety and reliability in deployment via arxiv · 12 Oct, 16:29	Not relevant Mathematical analysis of representation geometry, not practical AI safety, guardrails, or alignment.
The Ball and the Box: Two Geometries of Computation in Superposition Derives mathematical dimension thresholds required to compute Boolean gates using neural representations stored in superposition. Preprint	Small and efficient models via arxiv · 12 Oct, 16:29	Not relevant Explores theoretical representation capacity in superposition, not practical model compression or efficient serving.
The Ball and the Box: Two Geometries of Computation in Superposition Derives mathematical dimension thresholds required to compute Boolean gates using neural representations stored in superposition. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:29	Not relevant Theoretical analysis of Boolean computation in superposition, not LLM evaluation benchmarks or evaluation protocols.
SR-TTA: Spatial-Redundancy Test-Time Adaptation for Interference-Robust Respiration Sensing Proposes label-free test-time adaptation using spatial redundancy to improve respiration sensing on massive MIMO base stations against interference. Preprint	AI safety and reliability in deployment via arxiv · 12 Oct, 16:29	Not relevant Focuses on RF interference mitigation in wireless sensing, not AI model alignment or deployment safety risks.
SR-TTA: Spatial-Redundancy Test-Time Adaptation for Interference-Robust Respiration Sensing Proposes label-free test-time adaptation using spatial redundancy to improve respiration sensing on massive MIMO base stations against interference. Preprint	Small and efficient models via arxiv · 12 Oct, 16:29	Not relevant Addresses MIMO radar signal processing adaptation, not efficient model architectures or LLM compression.
SR-TTA: Spatial-Redundancy Test-Time Adaptation for Interference-Robust Respiration Sensing Proposes label-free test-time adaptation using spatial redundancy to improve respiration sensing on massive MIMO base stations against interference. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:29	Not relevant Presents wireless signal processing for vital sign sensing, not LLM evaluation or benchmarking methods.
Beyond QAOA: A Review of AI and Quantum Computing for Adaptive Combinatorial Optimization Reviews literature on adaptive combinatorial optimization combining machine learning policies with quantum computing workflows. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:29	Not relevant Reviews quantum computing and combinatorial optimization, not LLM evaluation or benchmark methodologies.
Beyond QAOA: A Review of AI and Quantum Computing for Adaptive Combinatorial Optimization Reviews literature on adaptive combinatorial optimization combining machine learning policies with quantum computing workflows. Preprint	Small and efficient models via arxiv · 12 Oct, 16:29	Not relevant Surveys quantum optimization algorithms, not neural network efficiency, distillation, or small language models.
Beyond QAOA: A Review of AI and Quantum Computing for Adaptive Combinatorial Optimization Reviews literature on adaptive combinatorial optimization combining machine learning policies with quantum computing workflows. Preprint	AI safety and reliability in deployment via arxiv · 12 Oct, 16:29	Not relevant Focuses on quantum combinatorial algorithms, not AI safety, red-teaming, hallucination, or operational guardrails.
RAGenome: Scaling Retrieval-Based Genomic Language Models to Long Contexts Presents a retrieval-augmented genomic language model scaling pretraining context length to capture long-range biological sequence interactions. Preprint	Small and efficient models via arxiv · 12 Oct, 16:29	Not relevant Focuses on scaling genomic models to long sequences, not model compression or small efficient architectures.
RAGenome: Scaling Retrieval-Based Genomic Language Models to Long Contexts Presents a retrieval-augmented genomic language model scaling pretraining context length to capture long-range biological sequence interactions. Preprint	AI safety and reliability in deployment via arxiv · 12 Oct, 16:29	Not relevant Applies retrieval to genomic biology, not AI deployment safety, alignment, or system guardrails.
RAGenome: Scaling Retrieval-Based Genomic Language Models to Long Contexts Presents a retrieval-augmented genomic language model scaling pretraining context length to capture long-range biological sequence interactions. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:29	Not relevant Introduces a retrieval-based genomic model, not an LLM evaluation dataset, benchmark, or evaluation methodology.
Optimal random quantisers for spherically symmetric distributions Analyzes optimal random quantisers for high-dimensional spherically symmetric distributions to reduce distortion with moderate sample sizes. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:29	Not relevant Focuses on mathematical quantization theory for probability distributions, not LLM benchmarks or evaluation methods.
Optimal random quantisers for spherically symmetric distributions Analyzes optimal random quantisers for high-dimensional spherically symmetric distributions to reduce distortion with moderate sample sizes. Preprint	Small and efficient models via arxiv · 12 Oct, 16:29	Not relevant Pure mathematical statistics on vector quantisation of symmetric distributions, not neural network compression or efficient inference.

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