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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

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

DGX agent

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

researcharxiv-cs-ai

29 May 2026

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

Mind-Omni: A Unified Multi-Task Framework for Brain-Vision-Language Modeling via Discrete Diffusion

arXiv:2605.29591v1 Announce Type: new Abstract: Modeling the interplay between external stimuli and internal neural representations is a pivotal research area for Brain-Computer Interfaces (BCIs). A m

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 Mechanisms: How Language Models Retrieve Bound Entities In-Context

arXiv:2510.06182v2 Announce Type: replace Abstract: A key component of in-context reasoning is the ability of language models (LMs) to bind entities for later retrieval. For example, an LM might repre

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

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

On Language Generation in the Limit with Bounded Memory

arXiv:2605.30324v1 Announce Type: cross Abstract: We study language generation in the limit under bounded memory. In this task, a learner observes examples from an unknown target language one at a tim

On the Optimizer Dependence of Neural Scaling Laws

arXiv:2605.29387v1 Announce Type: cross Abstract: The scaling exponent alpha in neural scaling laws L(N) propto N^{-alpha} is commonly treated as a fixed constant set by architecture and data. We pres

One Click per Cell Type Suffices: Training-free Group Interaction for Cell Instance Segmentation

arXiv:2605.29429v1 Announce Type: new Abstract: Cell instance segmentation models trained on cell-specific datasets suffer severe performance drops on out-of-distribution cell types, while interactive

Open World Autoencoding Drift Detection with Novel Class Recognition in Tabular Non-stationary Data Streams

arXiv:2605.29834v1 Announce Type: new Abstract: Data stream processing has become a landmark in modern machine learning applications, with concept drifts and novel class appearances posing the primary

Opt-Verifier: Unleashing the Power of LLMs for Optimization Modeling via Dual-Side Verification

arXiv:2605.29556v1 Announce Type: new Abstract: Building mathematical optimization models is critical in operations research (OR), while it requires substantial human expertise. Recent advancements ha

Optimal Gap-Dependent Regret for Private Stochastic Decision-Theoretic Online Learning

arXiv:2605.29148v1 Announce Type: new Abstract: We study stochastic decision-theoretic online learning with full information and event-level pure differential privacy. A COLT open problem of Hu and Me

Optimal Rates for Differentially Private Hypothesis Testing with E-values

arXiv:2605.28952v1 Announce Type: cross Abstract: E-values have attracted considerable interest in recent years as flexible tools for enabling anytime-valid and adaptive data analysis. Hypothesis test

Optimization and Generation in Aerodynamics Inverse Design

arXiv:2602.03582v3 Announce Type: replace Abstract: Aerodynamic inverse design can improve vehicle and aircraft efficiency, but practical design rarely seeks performance alone: vehicle refinement must

ParCo-SDF: Learning Prior-Free Partial-to-Complete Signed Distance Fields of Deformable Objects

arXiv:2605.29417v1 Announce Type: new Abstract: This study addresses the partial-to-complete geometry reconstruction of deformable objects (DOs) from point-cloud observations toward precise DO manipul

Phantom: Training Robots Without Robots Using Only Human Videos

arXiv:2503.00779v2 Announce Type: replace Abstract: Training general-purpose robots requires learning from large and diverse data sources. Current approaches rely heavily on teleoperated demonstration

researcharxiv-cs-ro