All entries

LLMs for Social Network Modeling: From Network Generation to Dynamic Processes

arXiv:2609.08049v1 Announce Type: cross Abstract: Large language models (LLMs) are rapidly emerging as a new paradigm for modeling social networks by representing users and their relationships and int

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

LOBERT: Generative AI Foundation Model for Limit Order Book Messages

DGX agent

arXiv:2511.12563v2 Announce Type: replace Abstract: Modeling the dynamics of financial Limit Order Books (LOB) at the message level is challenging due to irregular event timing, rapid regime shifts, a

researcharxiv-cs-ai

10 Sept 2026

Localizing and Correcting Errors for LLM-based Planners

arXiv:2602.00276v3 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated strong reasoning capabilities on math and coding, but frequently fail on symbolic classical planning

local-aiarxiv-cs-ai

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

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

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

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

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

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

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

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

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,

Myocardial Strain Drift Correction in Deep Learning Based Ultrasound Tracking

arXiv:2609.09577v1 Announce Type: cross Abstract: Myocardial strain from echocardiography is a key biomarker for cardiac function. Recent deep learning methods show strong performance for myocardial m

Neptune: An AI model for Global Ocean Subseasonal Prediction

arXiv:2609.08606v1 Announce Type: cross Abstract: Subseasonal-to-seasonal (S2S) forecasting is societally critical, supporting decision-making in sectors ranging from water and agricultural management