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Liquid Latent State Dynamics for Interpretable Turbofan Degradation Modeling

model-releasesarxiv-cs-lg

arXiv:2607.01986v1 Announce Type: new Abstract: Multivariate time-series models for prognostics are often evaluated by point prediction accuracy, yet their internal states rarely expose a coherent deg

LLM Priors for ERM over Programs

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DGX agent

arXiv:2510.14331v3 Announce Type: replace Abstract: We study program-learning methods that are efficient in both samples and computation. Classical learning theory suggests that when the target admits

researcharxiv-cs-lg

3 Jul 2026

LLMs as Teaching Assistants for Mathematics Exam Grading: Reliability, and Practical Usability

arXiv:2607.01247v1 Announce Type: cross Abstract: Open-ended mathematics exams are valuable because they assess reasoning, proof construction, algorithmic thinking, and communication of intermediate s

Local exponential stability of mean-field Langevin descent-ascent and associated particle system

arXiv:2602.01564v2 Announce Type: replace Abstract: We study the mean-field Langevin descent-ascent (MFL-DA), a coupled optimization dynamics on the space of probability measures for entropically regu

Locality-Aware Continual Unlearning for Diffusion Models

arXiv:2512.02657v2 Announce Type: replace-cross Abstract: Real-world deployment of text-to-image diffusion models requires continual concept removal as new privacy, copyright, or safety obligations ar

Low-Latency Task-Oriented Image Transmission with Opportunistic Spectrum Access

arXiv:2607.01921v1 Announce Type: cross Abstract: Communication systems designed for reliable data reconstruction, rather than task-oriented communication, typically rely on separate source and channe

Agents

Lynx: Progressive Speculative Quantization for accelerating KV Transfer in Long-Context Inference

arXiv:2607.01831v1 Announce Type: cross Abstract: Long-context inference is increasingly common in large language model (LLM) serving, driven by retrieval-augmented generation and agentic systems. In

agentsarxiv-cs-lg

MAGIK: Mapping to Analogous Goals via Imagination-enabled Knowledge Transfer

arXiv:2506.01623v4 Announce Type: replace Abstract: Humans excel at analogical reasoning - applying knowledge from one task to a related one with minimal relearning. In contrast, reinforcement learnin

Applications

ManipArena: Comprehensive Real-world Evaluation of Reasoning-Oriented Generalist Robot Manipulation

arXiv:2603.28545v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models and world-action models have emerged as central paradigms for general-purpose robotic intelligence, yet their em

applicationsarxiv-cs-ro

Many Voices, One Reward: Multi-Role Rubric Generation for LLM Judging and Reward Modeling

arXiv:2607.01830v1 Announce Type: new Abstract: Reliable reward and preference signals are critical for evaluating and optimizing large language models on open-ended tasks. Rubric-based judges offer a

Local Ai

Mapping Text to Multiplex Graph: Prompt Compression as Levy Walk-Guided Graph Pruning

arXiv:2607.01241v1 Announce Type: cross Abstract: Existing prompt compression methods treat text as flat token sequences, failing to capture the distributed nature of important information, which is o

local-aiarxiv-cs-ai

Mastermind: Strategy-grounded Learning for Repository-Scale Vulnerability Reproduction

arXiv:2607.01764v1 Announce Type: new Abstract: Repository-level vulnerability reproduction is a demanding software engineering (SE) task: an agent must inspect a codebase, infer the input grammar tha

Mean Field Reinforcement Learning

arXiv:2607.01525v1 Announce Type: cross Abstract: This monograph provides an introduction to mean field reinforcement learning through the lens of Markov decision processes arising from large-populati

safetyarxiv-cs-lg

Mechanistic Interpretability and Causal Feature Steering of Neural Quantum States via Sparse Autoencoders

arXiv:2607.01336v1 Announce Type: cross Abstract: Neural Quantum States (NQS) are a remarkably expressive class of variational ansatze for quantum many-body wavefunctions, yet little is understood abo

MedRepBench: A Comprehensive Benchmark for Medical Report Interpretation

arXiv:2508.16674v2 Announce Type: replace-cross Abstract: Medical report understanding from real-world document images is essential for generating patient-facing explanations and enabling structured i

MedStreamBench: A Time-Aware Benchmark for Streaming and Proactive Medical Video Understanding

arXiv:2607.01751v1 Announce Type: cross Abstract: Existing medical video benchmarks primarily evaluate whether a model produces the correct answer, but rarely assess whether it answers at the right ti

Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity

arXiv:2602.03315v2 Announce Type: replace Abstract: Agent memory systems must accommodate continuously growing information while supporting efficient, context-aware retrieval for downstream tasks. Abs

Message Passing Based Two-Timescale Bayesian Learning for Joint Channel and Memory Hardware Impairments Tracking

arXiv:2607.01660v1 Announce Type: new Abstract: Hardware impairments in massive multiple-input multiple-output (MIMO) receivers introduce inter-symbol memory and inter-element coupling, severely degra

Meta-Benchmarks for Financial-Services LLM Evaluation

arXiv:2607.01740v1 Announce Type: new Abstract: Public LLM leaderboards optimise for global average performance and do not capture the specific cognitive demands of financial-services work: a model th

Meta-Representational Predictive Coding: Neuroscience-Informed Self-Supervised Learning

arXiv:2503.21796v2 Announce Type: replace-cross Abstract: Self-supervised learning has become an increasingly important paradigm in the domain of machine intelligence. Furthermore, evidence for self-s

MetaTT: A Global Tensor-Train Adapter for Parameter-Efficient Fine-Tuning

arXiv:2506.09105v3 Announce Type: replace-cross Abstract: We present MetaTT, a Tensor Train (TT) adapter framework for fine-tuning of pre-trained transformers. MetaTT enables flexible and parameter-ef

MetaTune: Adjoint-based Meta-tuning via Robotic Differentiable Dynamics

arXiv:2603.27313v2 Announce Type: replace Abstract: Disturbance observer-based control has shown promise in robustifying robotic systems against uncertainties. However, tuning such systems remains cha

safetyarxiv-cs-ro

Mirror Illusion Art

arXiv:2607.02015v1 Announce Type: cross Abstract: Mirror Illusion Art is a novel reflection-conditioned 3D illusion where one object yields two target appearances (front and mirror). The task is formu

Mixture-of-Parallelisms: Towards Memory-Efficient Training Stack for Mixture-of-Experts Models

arXiv:2607.01844v1 Announce Type: cross Abstract: This paper showcases a memory-efficient training stack for Mixture-of-Experts (MoE) models. It is a training paradigm that combines and specializes va

MKGR: Multimodal Knowledge-Graph Representation Learning for Cold-Start Protein-Protein Interaction Prediction

arXiv:2607.01627v1 Announce Type: cross Abstract: Accurate protein-protein interaction (PPI) prediction is central to functional genomics, disease mechanism discovery, and drug development. A difficul

Agents

MMAO-Cls: Metabolic Multi-Agent Optimization for Joint Feature Selection and Classifier Tuning

arXiv:2607.01539v1 Announce Type: cross Abstract: This paper studies whether the Metabolic Multi-Agent Optimizer (MMAO) can act as a credible outer-loop optimizer for classification model selection. W

agentsarxiv-cs-lg

MMBench-Live: A Continuously Evolving Benchmark for Multimodal Models

arXiv:2607.01813v1 Announce Type: cross Abstract: Evaluation benchmarks are essential for assessing vision-language models (VLMs), but most multimodal benchmarks are static, making them vulnerable to

MMIR-TCM: Memory-Integrated Multimodal Inference and Retrieval for TCM Clinical Decision Support

arXiv:2607.01814v1 Announce Type: new Abstract: Traditional Chinese Medicine (TCM) diagnosis, particularly through tongue inspection, faces persistent challenges in subjectivity and reproducibility. T

Model Merging as Probabilistic Inference in Fine-Tuning Parameter Space

arXiv:2607.01689v1 Announce Type: cross Abstract: Model merging aims to combine existing single-task solutions into a multi-task solution without additional data-driven fine-tuning.~Most existing appr

MolSight: A Graph-Aware Vision-Language Model for Unified Chemical Image Understanding

arXiv:2607.01982v1 Announce Type: cross Abstract: Using molecular large language models (LLMs) as a unified framework for understanding molecular structures and functions is emerging as a new trend in

Morphology-Aware Sample Assignment: Overcoming IoU Insensitivity for Surface Defect Detection

arXiv:2606.13723v2 Announce Type: replace-cross Abstract: Intersection-over-Union (IoU), as a pivotal metric for evaluating the spatial alignment between candidate proposals and ground-truth annotatio

Applications

Motion-Focused Latent Action Enables Cross-Embodiment VLA Training from Human EgoVideos

arXiv:2606.18955v2 Announce Type: replace-cross Abstract: Training generalist Vision-Language-Action(VLA) models typically requires massive, diverse robotic datasets with high-fidelity action annotati

applicationsarxiv-cs-ro

MultAttnAttrib: Training-Free Multimodal Attribution in Long Document Question Answering

arXiv:2607.01420v1 Announce Type: cross Abstract: As grounded QA systems are increasingly deployed in AI assistants, accurately attributing generated answers to evidence is critical for user trust and

Multi-Head Recurrent Memory Agents

arXiv:2607.01523v1 Announce Type: cross Abstract: Recurrent memory agents extend LLMs to arbitrarily long contexts by iteratively consolidating input into a fixed-size memory window. Despite their sca

Multi-modal Rail Crossing Safety Analysis

arXiv:2607.01365v1 Announce Type: cross Abstract: Given one or more images of a railway crossing, can we leverage visual cues that allow us to robustly estimate how safe it is? Can we improve our abil

Multi-Objective Exploration and Preference Optimization via Mutual Information

arXiv:2607.01392v1 Announce Type: new Abstract: Aligning large language models with diverse and heterogeneous human values requires multi-objective alignment methods to effectively trade off conflicti

safetyarxiv-cs-cl

Multi-Rate Nonlinear Model Predictive Control for Wall-Supported Bipedal Locomotion of Quadrupedal Robots

arXiv:2607.01574v1 Announce Type: new Abstract: This paper presents a novel layered planning and control framework based on multi-rate nonlinear model predictive control (MR-NMPC) that enables quadrup

researcharxiv-cs-ro

Multilayer Q-Matrix-Embedded Neural Network for Cognitive Diagnosis (M-QCDNet): Structure-Aware Deep Learning Architecture for Psychometric Interpretability

arXiv:2607.01278v1 Announce Type: new Abstract: The research proposes a multilayer Q-matrix-embedded neural network for cognitive diagnosis (M-QCDNet), which integrates the structural interpretability

safetyarxiv-cs-lg

Multilingual Prompt Localization for Agent-as-a-Judge: Language and Backbone Sensitivity in Requirement-Level Evaluation

arXiv:2604.04532v2 Announce Type: replace-cross Abstract: Evaluation language is typically treated as a fixed English default in agentic code benchmarks, yet we show that changing the judge's language

Local Ai

Multimodal Knowledge Edit-Scoped Generalization for Online Recursive MLLM Editing

arXiv:2607.01978v1 Announce Type: new Abstract: Online multimodal knowledge editing requires injecting a continual stream of visual-textual corrections into multimodal large language models (MLLMs) wi

local-aiarxiv-cs-ai

mupscaling small models: Principled warm starts and hyperparameter transfer

arXiv:2602.10545v2 Announce Type: replace-cross Abstract: Modern large-scale neural networks are often trained and released in multiple sizes to accommodate diverse inference budgets. To improve effic

NarrativeTrack: Evaluating Entity-Centric Reasoning for Narrative Understanding

model-releasesarxiv-cs-lg

arXiv:2601.01095v3 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) have achieved impressive progress in vision-language reasoning, yet their ability to understand tempo

NAVER LABS Europe Submission to the Instruction-following 2026 Short Track

arXiv:2607.01960v1 Announce Type: new Abstract: In this paper, we describe NAVER LABS Europe's submission to the instruction-following speech processing short track at IWSLT 2026. We participate again

researcharxiv-cs-cl

Navigating the Alignment-Calibration Trade-off: A Pareto-Superior Frontier via Model Merging

arXiv:2510.17426v3 Announce Type: replace-cross Abstract: The 'alignment tax' of post-training is typically framed as a drop in task accuracy. We show it also involves a severe loss of calibration, ma

NeoMap: Training-free Novel-View Synthesis from Single Images and Videos

arXiv:2607.01962v1 Announce Type: cross Abstract: We study the challenging problem of novel view video synthesis from single images or monocular videos. Existing methods, which operate under the assum

Neuro-Symbolic Safety Guidance for Vision-Language-Action Models via Constrained Flow Matching

model-releasesarxiv-cs-ro

arXiv:2607.01378v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated promising generalization capabilities across robotic manipulation tasks, yet their real-world depl

NeuroBridge: Bridging Multi-Task MRI Knowledge for Neurodegenerative Disease Diagnosis

arXiv:2607.01401v1 Announce Type: cross Abstract: INTRODUCTION: Accurate MRI-based identification of Alzheimer's disease (AD), mild cognitive impairment (MCI), and related dementias remains challengin

Neuron-Aware Active Few-Shot Learning for LLMs

arXiv:2607.02423v1 Announce Type: cross Abstract: Active Few-Shot Learning (AFSL) adapts LLMs to specialized domains by identifying the most valuable unlabeled samples for annotation and use as few-sh