Search: “research”

Lightweight Multimodal LLM-Enabled Cost-Effective Defect Grading of Power Transmission Equipment

arXiv:2605.28822v1 Announce Type: new Abstract: Defect grading of power transmission equipment (DGPTE) is crucial to the stability of electric energy transmission. Although existing machine learning m

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Research

LLMBridge: An LLM Pipeline for End-to-end Referential Bridging Resolution in English

DGX agent

arXiv:2605.29048v1 Announce Type: new Abstract: In this paper, we introduce LLMBridge, a new LLM based system for the task of end-to-end referential bridging resolution in English. Our bridging resolu

researcharxiv-cs-cl

29 May 2026

LLMSurgeon: Diagnosing Data Mixture of Large Language Models

arXiv:2605.30348v1 Announce Type: cross Abstract: The pretraining data mixture of Large Language Models (LLMs) constitutes their 'digital DNA', shaping model behaviors, capabilities, and failure modes

LoRe: Adaptive Interaction-Evaluation Routing with Per-Step Interaction Budgets for Iterative Graph Solvers

arXiv:2605.29005v1 Announce Type: cross Abstract: Diffusion-based neural solvers for combinatorial optimization repeatedly re-evaluate dense edge/factor interactions, making inference expensive in wal

Manifold-based Algorithms for the Hadamard Decomposition

arXiv:2605.28980v1 Announce Type: cross Abstract: Given a matrix X, and two ranks r_1 and r_2, the Hadamard decomposition (HD) looks for two low-rank matrices, X_1 of rank r_1 and X_2 of rank r_2, bot

MARTIAN: A Rendering Framework for Aerial Mars Imagery from HiRISE Orbital Data

arXiv:2605.29647v1 Announce Type: new Abstract: Aerial navigation on Mars requires vision-based pipelines that are robust to the diverse illumination conditions and terrain morphology of the Martian s

Masked Diffusion Vision-Language Models for Temporal Action Localization

arXiv:2605.29858v1 Announce Type: new Abstract: Temporal action localization (TAL) requires recognizing the target event and localizing its start and end times precisely in untrimmed videos. Recent vi

Matching Rates and Optimal Allocation for Federated Probe-Logit Distillation under Heterogeneous Bandwidth Budgets

arXiv:2605.29642v1 Announce Type: cross Abstract: In federated language modeling, K nodes each hold n samples but cannot pool data or exchange full-precision gradients or weights. We study the minimax

Matrix Completion with Hypergraphs:Sharp Thresholds and Efficient Algorithms

arXiv:2401.08197v3 Announce Type: replace Abstract: This paper considers the problem of completing a rating matrix based on sub-sampled matrix entries as well as observed social graphs and hypergraphs

Measure flow path recovery in Bayes Hilbert spaces

arXiv:2603.20329v2 Announce Type: replace-cross Abstract: We study the ill-posed problem of recovering a probability measure flow from finitely many moving localized sensors using a Bayes Hilbert fram

MEC: Machine-Learning-Assisted Generalized Entropy Calibration for Semi-Supervised Mean Estimation

arXiv:2604.05446v2 Announce Type: replace-cross Abstract: Obtaining high-quality labels is costly, whereas unlabeled covariates are often abundant, motivating semi-supervised inference methods with re

Mechanism Shift During Post-training from Autoregressive to Masked Diffusion Language Models

arXiv:2601.14758v4 Announce Type: replace-cross Abstract: Post-training pretrained autoregressive models (ARMs) into masked diffusion models (MDMs) has emerged as a cost-effective way to overcome the

MedCase-Structured: A Text-to-FHIR Dataset for Benchmarking Diagnostic Reasoning in Clinically Realistic EHR Settings

arXiv:2605.30295v1 Announce Type: cross Abstract: Large language models (LLMs) show promise for clinical reasoning and decision support, but evaluation in realistic, electronic health record-congruent

MELD: Mel-Spectrogram-Based Speech Language Modeling with Discrete Latent Variables

arXiv:2605.29859v1 Announce Type: cross Abstract: Recent speech language models rely on encoders that are optimized separately from autoregressive models. Since these encoders are unaware of the downs

MemoSight: Unifying Context Compression and Multi Token Prediction for Reasoning Acceleration

arXiv:2604.14889v2 Announce Type: replace Abstract: While chain-of-thought (CoT) reasoning enables LLMs to solve challenging reasoning tasks, the linear growth of the KV cache leads to substantial mem

Mesh-Aware Epipolar Matching for Multi-View Multi-Person 3D Pose Estimation in Basketball

arXiv:2605.29953v1 Announce Type: new Abstract: Multi-view multi-person 3D pose estimation in team sports scenarios remains challenging due to player occlusions, appearance similarity caused by team u

Meta-Programming for Linear-time Temporal Answer Set Programming

arXiv:2605.29965v1 Announce Type: new Abstract: The development of temporal extensions of Answer Set Programming (ASP) has led to the emergence of non-monotonic linear-time (TEL), dynamic (DEL), and m

MiAD: Mirage Atom Diffusion for De Novo Crystal Generation

arXiv:2511.14426v2 Announce Type: replace-cross Abstract: In recent years, diffusion-based models have demonstrated exceptional performance in searching for simultaneously stable, unique, and novel (S

Micro-Macro Retrieval: Reducing Long-Form Hallucination in Large Language Models

arXiv:2605.28828v1 Announce Type: cross Abstract: Large Language Models (LLMs) achieve impressive performance across many tasks but remain prone to hallucination, especially in long-form generation wh

Midpoint Generative Models

arXiv:2605.29920v1 Announce Type: new Abstract: We introduce Midpoint Generative Models (MGM), a principled framework for training one-step generative models. MGM is based on a simple symmetry of Flow

Mindscape-Aware Retrieval Augmented Generation for Improved Long Context Understanding

arXiv:2512.17220v2 Announce Type: replace Abstract: Humans understand long and complex texts by relying on a holistic semantic representation of the content. This global view helps organize prior know

minWM: A Full-Stack Open-Source Framework for Real-Time Interactive Video World Models

arXiv:2605.30263v1 Announce Type: new Abstract: Recent video diffusion foundation models have achieved remarkable progress in high-quality video generation, yet turning them into real-time interactive

MIRA: Mid-training Rubric Anchoring for Source-Aware Data Selection

arXiv:2605.30288v1 Announce Type: new Abstract: Mid-training has become an important stage in modern LLM development, using large-scale curated mixtures to strengthen capabilities before final post-tr

MIRAGE: Adaptive Multimodal Gating for Whole-Brain fMRI Encoding

arXiv:2605.29850v1 Announce Type: new Abstract: Recent progress in task-optimized neural networks has established encoding models as a powerful tool for predicting brain responses to naturalistic stim

Mixing Vector Model for Copolymer Inference via Mixed Integer Linear Programming

arXiv:2605.29329v1 Announce Type: cross Abstract: A novel two-phase molecule inference framework, mol-infer, has recently been developed to infer chemical graphs with prescribed abstract structures an

MMTM: Tri-Modal Topic Modeling for Long-Form Video via Similarity-Gated Fusion

arXiv:2605.29765v1 Announce Type: new Abstract: We introduce MMTM, a modular pipeline for topic discovery in long-form video that integrates speech recognition, audio and visual embeddings, and BERTop

Model Merging by Output-Space Projection

arXiv:2605.29101v1 Announce Type: new Abstract: Model merging combines fine-tuned checkpoints into a single multi-task model without retraining. Existing methods - such as task arithmetic, model soups

Moment-KV: Momentum-Based Decode-Time KV Cache Compression for Long Generation

arXiv:2605.29873v1 Announce Type: new Abstract: Key-Value (KV) cache remains a major bottleneck for deploying Large Language Models (LLMs) in long-generation tasks. Prior work often applies uniform co

Moment Matching Q-Learning

arXiv:2605.29033v1 Announce Type: new Abstract: Score-based and flow-based generative models exhibit remarkable expressive capacity in capturing complex distributions, and have been extensively deploy

Momentum Based Reward Design for Low Emission Traffic Signal Control

arXiv:2605.29693v1 Announce Type: new Abstract: Urban traffic congestion is a growing global issue contributing significantly to long commute times and environmental pollution. Traditional traffic sig

MoSSP: A Momentum-Based Single-Loop Stochastic Penalty Method for Nonconvex Constrained DC-Regularized Optimization

arXiv:2605.29635v1 Announce Type: cross Abstract: In this paper, we study a structured class of nonconvex constrained stochastic problems with difference-of-convex (DC) regularization, where the feasi

Multi-Stage VLM Pipeline for Zero-Shot Traffic Accident Understanding

arXiv:2605.29325v1 Announce Type: new Abstract: We present the 1st-place solution to the ACCIDENT challenge at the CVPR 2026 AUTOPILOT Workshop, which asks for zero-shot prediction of accident timing,

Multifingered force-aware control for humanoid robots

arXiv:2603.08142v2 Announce Type: replace Abstract: In this paper, we address force-aware control and force distribution in robotic platforms with multi-fingered hands. Given a target goal and force e

researcharxiv-cs-ro

Muscle Synergy Priors Enhance Biomechanical Fidelity in Predictive Musculoskeletal Locomotion Simulation

arXiv:2603.10474v2 Announce Type: replace Abstract: Human locomotion emerges from high-dimensional neuromuscular control, making predictive musculoskeletal simulation challenging. We present a physiol

MVP-Shapley: Feature-based Modeling for Evaluating the Most Valuable Player in Basketball

arXiv:2506.04602v4 Announce Type: replace-cross Abstract: The burgeoning growth of the esports and multiplayer online gaming community has highlighted the critical importance of evaluating the Most Va

Neural-Behavioral Representation of Natural Whole-body Movement in Monkeys

arXiv:2605.29355v1 Announce Type: new Abstract: Understanding how cortical activity represents natural whole-body behaviors in primates remains challenging. Limited by the diversity of movements and i

Neural Networks and (Virtual) Extended Formulations

arXiv:2411.03006v4 Announce Type: replace-cross Abstract: Neural networks with piecewise linear activation functions, such as rectified linear units (ReLU) or maxout, are among the most fundamental mo

Neural Scaling Laws for Jet Generation

arXiv:2605.28940v1 Announce Type: cross Abstract: Recently observed empirical scaling laws describe the performance of foundation-type models as three independent key quantities -- dataset size, compu

NeuroEdge: Real-Time Hand Gesture Recognition with High-Density EMG Using Deep Learning at the Edge

arXiv:2605.29326v1 Announce Type: new Abstract: High-density electromyography (HD-EMG) has emerged as a powerful modality for decoding fine-grained neuromuscular activity, enabling real-time neural-ma

Nine Judges, Two Effective Votes: Correlated Errors Undermine LLM Evaluation Panels

arXiv:2605.29800v1 Announce Type: new Abstract: LLM-as-a-judge panels aggregate votes from multiple models, with the expectation that diverse models yield more reliable evaluations. We develop a frame

Noise-Aware Differentially Private Variational Inference

arXiv:2410.19371v3 Announce Type: replace-cross Abstract: Differential privacy (DP) provides robust privacy guarantees for statistical inference, but this can lead to unreliable results and biases in

Non-Euclidean Gradient Descent Operates at the Edge of Stability

arXiv:2603.05002v2 Announce Type: replace Abstract: The Edge of Stability (EoS) is a phenomenon where the sharpness (largest eigenvalue) of the Hessian approaches and then hovers near the stability th

Non-Forgetting Knowledge Allocation with Bi-level Competition for Class-Incremental Learning

arXiv:2605.29592v1 Announce Type: new Abstract: Class-Incremental Learning (CIL) with pre-trained models (PTMs) aims to sequentially adapt PTMs to new categories without forgetting old knowledge. Buil

OccamToken: Efficient VLM Inference with Training-Free and Budget-Adaptive Token Pruning

arXiv:2605.29657v1 Announce Type: cross Abstract: Vision-language models (VLMs) rely on long visual token sequences for visual understanding, making the prefill stage expensive in both computation and

OmniCD: A Foundational Framework for Remote Sensing Image Change Detection Guided by Multimodal Semantics

arXiv:2605.30168v1 Announce Type: new Abstract: Change detection (CD) in remote sensing is vital for applications such as urban monitoring and disaster assessment, yet traditional methods struggle wit

OmniCustom: Sync Audio-Video Customization Via Joint Audio-Video Generation Model

arXiv:2602.12304v4 Announce Type: replace-cross Abstract: Existing mainstream video customization methods focus on generating identity-consistent videos based on given reference images and textual pro

Model Releases

OmniMatBench: A Human-Calibrated Multimodal Reasoning Benchmark Across 19 Materials Science Subfields

model-releasesarxiv-cs-ai

arXiv:2605.29833v1 Announce Type: new Abstract: As multimodal language models play an increasingly important role in scientific research, materials science offers a critical testbed due to its interdi

On Asymmetric Optimization of Reasoning and Perception in Vision-Language Model Post-Training

arXiv:2605.29496v1 Announce Type: new Abstract: Post-training has greatly improved reasoning in frontier vision-language models, yet its gains for perception remain comparatively limited, creating a b