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LogicSkills: A Structured Benchmark for Formal Reasoning in Large Language Models

arXiv:2602.06533v3 Announce Type: replace Abstract: Large language models perform well on many logical reasoning benchmarks, but it remains unclear which core logical skills they truly master. To addr

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LogiScope-VQA: Benchmarking Vision-Language Models for Logistics Hazard Identification in Industrial Scenarios

DGX agent

arXiv:2609.09790v1 Announce Type: cross Abstract: Large Multimodal Models (LMMs) large-scale deployment in industrial warehouse settings specifically necessitates that models exhibit human-expert-leve

model-releasesarxiv-cs-cl

10 Sept 2026

Longitudinal tracking of multiple sclerosis lesions in the spinal cord: A validation study

arXiv:2609.09424v1 Announce Type: new Abstract: Longitudinal characterization of multiple sclerosis (MS) lesions remains constrained by the lack of frameworks capable of establishing consistent instan

Looped GPT-BERT: Trading Parameters for Computation in Small Language Modeling

arXiv:2609.09691v1 Announce Type: new Abstract: When training data are limited, increasing parameter count is not the only way to improve language-model performance. A small parameter set, when repeat

Low-Rank Prompt Learning for Vision-Language Models with Fixed-Token Bases

arXiv:2609.09462v1 Announce Type: new Abstract: Prompt learning adapts CLIP to downstream recognition by replacing hand-written templates with learned continuous context vectors, which in Context Opti

LSP-DETR: Efficient and Scalable Nuclei Segmentation in Whole-Slide Images

arXiv:2601.03163v2 Announce Type: replace Abstract: Background and Objective: Precise and scalable instance segmentation of cell nuclei is a fundamental prerequisite for computational pathology, yet g

local-aiarxiv-cs-cv

M2LG-DG: A Multi-modal Local-Global Domain Generalization Framework for Cross-site Major Depressive Disorder Classification

arXiv:2609.09186v1 Announce Type: new Abstract: Classification models based on resting-state functional magnetic resonance imaging (rs-fMRI) often show lower performance at imaging sites not included

MADS: Multi-Agent Dialogue Simulation for Diverse Persuasion Data Generation

arXiv:2510.05124v3 Announce Type: replace Abstract: We propose MADS (Multi-Agent Dialogue Simulation), a scalable framework for generating persuasive multi-turn dialogues via agent self-play. MADS emp

agentsarxiv-cs-cl

Manifold-Aligned Generative Transport

arXiv:2602.19600v2 Announce Type: replace-cross Abstract: Many high-dimensional datasets concentrate near a low-dimensional structure embedded in the ambient space. Generative models for such data mus

safetyarxiv-cs-lg

Mapping the Emerging Social Science of Large Language Models

arXiv:2609.07598v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly shape communication, learning, work, creativity, and decision-making, yet social-science research on these d

safetyarxiv-cs-ai

Marker-free eye-gaze estimation using a single image and depth from defocus

arXiv:2609.09610v1 Announce Type: new Abstract: This paper presents a marker-free eye-gaze estimation approach using a single 2D camera, such as an integrated laptop webcam. The gaze-related features

Mathematical Programming in Machine Learning and Artificial Intelligence: A Unified Taxonomy of Models and Applications

arXiv:2609.07254v1 Announce Type: cross Abstract: Mathematical programming provides a common language for many decisions embedded in modern machine-learning (ML) and artificial-intelligence (AI) syste

Industry

Mathematicians want proof OpenAI didn’t use their work

Another researcher is challenging OpenAI about the data driving its increasingly impressive array of mathematical discoveries. Just days after a bitter row erupted over whether the company's models be

industrythe-verge-ai

Maverick: Private and Verifiable LLM Inference Made Practical via Matrix-Vector Multiplication Delegation

arXiv:2609.10264v1 Announce Type: cross Abstract: Open-source large language models (LLMs) are increasingly competitive with closed-source models while offering transparency and the ability to run inf

local-aiarxiv-cs-lg

May, damn it, not six weeks. Senior, not entry level.

May, damn it, not six weeks. Senior, not entry level. Jacob was a senior researcher who joined Anthropic in May. My Anthropic colleagues and I had been trying to recruit him for ~2 years, because we k

safetygary-marcus--x

Measuring LLM Sycophancy under Sustained Multi-Turn Pressure

arXiv:2609.09090v1 Announce Type: cross Abstract: Large language models (LLMs) may abandon correct positions when users push back, exhibiting a failure mode known as sycophancy. Existing evaluations t

MeClear: Cooperative Game-Theoretic Attribution and Risk-Aware Memory Clearance for Long-Horizon LLM Agents

arXiv:2609.09115v1 Announce Type: new Abstract: Long horizon Large Language Model (LLM) agents rely on external memory systems to preserve user preferences and task knowledge across extended interacti

agentsarxiv-cs-ai

MedDeID enables locally governed clinical-text de-identification from real or synthetic training data

arXiv:2609.10049v1 Announce Type: new Abstract: Clinical notes contain personally identifiable information (PII), restricting reuse for research and medical AI, especially when data cannot leave an in

MemForest: Efficient Agent Memory Management via EventTree Partitioning and Progressive Merging

arXiv:2609.08273v1 Announce Type: new Abstract: Agent memory systems have demonstrated significant potential in long-term dialogue, personalized assistants, and video understanding. However, continuou

agentsarxiv-cs-ai

Meta-LinEXP3: Online-within-Online Learning for Adversarial Linear Contextual Bandits

arXiv:2609.09907v1 Announce Type: new Abstract: Meta-learning has emerged as an effective paradigm for transferring knowledge across sequential bandit tasks. While substantial progress has been made f

safetyarxiv-cs-lg

MethaneFuse: Learning from Multi-Sensor Satellite Observations for Methane Plume Detection

arXiv:2609.09762v1 Announce Type: new Abstract: Methane plume detection from satellite imagery is constrained by incomplete observations: public satellites provide complementary spatial, spectral, and

MetroLLM-Bench: Evaluating Language Models as Transit Kiosk Runtimes

arXiv:2609.10016v1 Announce Type: cross Abstract: We introduce MetroLLM-Bench, a 955-case benchmark for testing language models as the policy layer of a transit kiosk. It covers six real metro systems

Microcanonical Hamiltonian Monte Carlo and the Helmholtz Theorem

arXiv:2609.07620v1 Announce Type: cross Abstract: The recently proposed Microcanonical Hamiltonian Monte Carlo algorithm has not yet been studied in detail from a thermodynamic point of view; this wor

MiNCE: Nonparametric, Strongly Consistent Confidence Envelopes for Band-Limited Functions and their Smoothed Spectra

arXiv:2609.09436v1 Announce Type: cross Abstract: Minimum-norm confidence envelope strategies offer a nonparametric approach to constructing nonasymptotic, simultaneous confidence regions for band-lim

researcharxiv-cs-lg

Mind the Gap: Exposing LLM Translation Blind Spots Using the AlphaMWE Multilingual Parallel Corpus

arXiv:2609.06634v1 Announce Type: cross Abstract: LLMs' performance on machine translation (MT) tasks is often dependent on the data availability in the specific domains and language pairs that they a

Mini-Batch Risk-Averse Deep Q-Learning: A Robot Navigation Case Study

arXiv:2609.07998v1 Announce Type: new Abstract: We study the control of Markov decision processes in which the quality of a policy is evaluated by a dynamic, time-consistent Markov risk measure rather

safetyarxiv-cs-ai

Industry

MINT is now open source. From first-person RGB video, MINT reconstructs 3D camera trajectories and bimanual hand motion in a shared world co…

MINT is now open source. From first-person RGB video, MINT reconstructs 3D camera trajectories and bimanual hand motion in a shared world coordinate system. Reconstructed human hand motion can also be

industryemad-mostaque--x

MLLMs Hallucinate when Information Distribution Drifts in Synergy Heads

arXiv:2609.09206v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) often struggle with hallucinations, thus hindering their reliable practical applications. Existing attention-

researcharxiv-cs-cl

Mode Coverage in Normalizing Flow Boltzmann Generators via Log-Ratio Variation

arXiv:2609.09473v1 Announce Type: cross Abstract: Normalizing flow Boltzmann generators retain a tractable pushforward density, but training with forward KL depends on target samples that may be biase

researcharxiv-cs-lg

Industry

Model-agnostic PII detection with LLMs

A configurable, model-agnostic detector that turns any large language model on Amazon Bedrock into a PII detector. Because the entities to detect live in a prompt rather than in code, one detector ada

industryaws-ml-blog

Modus Tollens and Counterfactuals and Counterfactual Reasoning Based on Three Types of Negation

arXiv:2609.07483v1 Announce Type: new Abstract: Modus Tollens (MT) is a classical logical inference rule, while counterfactuals are hypothetical statements that are contrary to facts, and counterfactu

Monadic Second-Order Logic in HOL: Deep and Shallow with Automated Faithfulness (Extended Preprint)

arXiv:2609.07345v1 Announce Type: cross Abstract: In Isabelle/HOL, we apply the deep-and-shallow embedding methodology of our prior work to monadic second-order logic (MSO). Three embeddings are devel

local-aiarxiv-cs-ai

Monte Carlo-Based Ex-Ante Assessment of the Green Benefits of an AI-Driven Smart Agriculture Platform in Hainan

arXiv:2609.06737v1 Announce Type: new Abstract: Smart agriculture platforms are widely regarded as key carriers for implementing China's pesticide and fertilizer reduction, water-saving and carbon-red

More Than Mimicking Reviewers: Evaluating LLMs for Pre-Submission Peer Review

arXiv:2609.05788v1 Announce Type: new Abstract: Peer-review feedback often arrives too late for authors to make meaningful revisions. We study an author-facing LLM system that moves part of this stres

Morphological Decoupling-Based Skeletal Classification for Clinical Assessment of Malocclusion

arXiv:2609.09801v1 Announce Type: cross Abstract: Malocclusion skeletal grading is a fundamental task in orthodontics, critical for diagnosis and treatment planning. Traditionally, cone-beam computed

MOSAIC: A Universal Agent-Level Interface for Cross-Paradigm Agent Mixing and Human-AI Collaboration

model-releasesarxiv-cs-lg

arXiv:2603.01260v2 Announce Type: replace Abstract: Existing infrastructure cannot deploy agents from different decision-making paradigms within the same environment, making fair cross-paradigm compar

MotionBlind: Probing the Illusion of Motion Understanding in Video-LLMs

model-releasesarxiv-cs-cv

arXiv:2609.09528v1 Announce Type: new Abstract: Video large language models (Video-LLMs) are increasingly used as the perceptual front end of world models, a role that assumes they can read motion: ho

MUCnoHARM@GermEval Shared Task 2026: Retrieval-based In-Context Learning for Defamatory Offences, and Where It Falls Short

arXiv:2609.09791v1 Announce Type: new Abstract: With hate speech being ubiquitous online, automatic detection is crucial, in particular when it comes to criminally relevant social media posts. We stud

agentsarxiv-cs-cl

MuJoCable: Reduced-Order Surface-Routed Cable Transmission for Tendon-Driven Robots

arXiv:2609.09612v1 Announce Type: new Abstract: Tendon transmissions reduce distal inertia and add compliance, yet routing, slack, and friction govern motion and force transfer. Mainstream rigid-body

researcharxiv-cs-ro

Multi-Agent Reinforcement Learning for Autonomous UAV Exploration in Wildfire Response

arXiv:2609.10433v1 Announce Type: cross Abstract: This study develops a deep reinforcement learning framework for training Unmanned Aerial Vehicle (UAV) agents to navigate and monitor simulated wildfi

safetyarxiv-cs-lg

Multi-dimensional Preference Alignment by Conditioning Reward Itself

arXiv:2512.10237v2 Announce Type: replace Abstract: Reinforcement Learning from Human Feedback has emerged as a standard for aligning diffusion models. However, we identify a fundamental limitation in

safetyarxiv-cs-cv

Multi-Functional Embedding Models for Funder Name Disambiguation in Scientific Publication Records

arXiv:2609.09984v1 Announce Type: new Abstract: Understanding the historical allocation and distribution of research funding advances our knowledge of how scientific research is supported across field

Multi-Pass, Multi-View Blended Learning for High-Fidelity Volumetric CT Synthesis from Chest X-Rays

arXiv:2609.09920v1 Announce Type: new Abstract: Reconstructing volumetric Computed Tomography (CT) from a single 2D chest radiograph (CXR) is an ill-posed inverse problem, further complicated by the s

researcharxiv-cs-lg

Multi-Robot Scanner for Automated Full-Body Dermoscopic Imaging

arXiv:2609.10169v1 Announce Type: new Abstract: This paper outlines the specifications and design approach used to construct a full body imaging scanner capable of capturing skin lesions at a dermatos

researcharxiv-cs-ro

Multimodal Emotion Recognition in Conversations via Class-Wise Adaptive Modality Fusion and Affective Geometry

arXiv:2609.09924v1 Announce Type: new Abstract: Emotion Recognition in Conversations (ERC) requires integrating heterogeneous textual, audio, and visual cues while accounting for conversational contex

Muon-C: Operator-Aligned Muon for Convolutional Kernels

arXiv:2609.09676v1 Announce Type: new Abstract: Muon replaces matrix momentum with an approximately orthogonal polar direction, but its geometry depends on the matrix representation. For convolution,

local-aiarxiv-cs-lg

Muse-glimmer-30b really punches above its weight(s) for creative writing

model-releasesr-localllama

After noticing that it is ranked among MUCH larger frontier models in the EQ-Bench Creative Writing benchmark and the Hemingway-bench, I decided to give it a try and was very impressed. I didn't do ve

MVFA: A Multi-View Text-Guided Multimodal Fusion LLM Adapter for Sentiment Analysis and Emotion Recognition

arXiv:2609.06188v1 Announce Type: new Abstract: Multimodal sentiment analysis and emotion recognition in conversations demand effective modeling of heterogeneous interactions across textual, acoustic,