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MASTE: A Multi-Agent Pipeline for Zero-Shot Aspect Sentiment Triplet Extraction

arXiv:2607.08080v1 Announce Type: new Abstract: Aspect Sentiment Triplet Extraction (ASTE) requires jointly identifying (aspect, opinion, sentiment) triples from a given review sentence. While large l

agentsarxiv-cs-cl

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MatBind: A Shared Embedding Space for Multimodal Materials Characterization

DGX agent

arXiv:2607.08470v1 Announce Type: new Abstract: Fully characterizing a crystalline material requires integrating heterogeneous data sources -- atomic structures, diffraction patterns, electronic densi

safetyarxiv-cs-lg

10 Jul 2026

Maximum Mean Discrepancy with Unequal Sample Sizes via Generalized U-Statistics

arXiv:2512.13997v2 Announce Type: replace-cross Abstract: Existing two-sample testing techniques, particularly those based on choosing a kernel for the Maximum Mean Discrepancy (MMD), often assume equ

Mechanistic Interpretability of LLM Jailbreaks via Internal Attribution Graphs

arXiv:2607.07903v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit remarkable capabilities but remain highly vulnerable to adversarial prompts and jailbreak attacks. Existing appro

MentalHospital: A Virtual Environment for Evaluating Psychiatric Clinical Encounters

arXiv:2607.08257v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong performance on isolated psychiatric tasks, including dialogue, diagnosis, and treatment planning, yet exi

MetaHGNIE: Meta-Path Induced Hypergraph Contrastive Learning in Heterogeneous Knowledge Graphs

arXiv:2512.12477v2 Announce Type: replace Abstract: Estimating node importance in heterogeneous knowledge graphs is a fundamental problem underlying recommendation, search, and knowledge decision syst

Metrics or Mirage? An Audit of Evaluation Inconsistencies in Colonoscopy Polyp Segmentation Benchmarks

arXiv:2607.08203v1 Announce Type: new Abstract: Progress in colonoscopy polyp segmentation is routinely reported through leaderboard comparisons on a small set of public benchmarks. We argue that this

researcharxiv-cs-cv

Mixture of Enhanced-View Experts for Multi-Query Vehicle ReID and A Large-Scale Benchmark

model-releasesarxiv-cs-cv

arXiv:2607.08085v1 Announce Type: new Abstract: Multi-query vehicle ReID aims to leverage complementary information from diverse views for robust feature learning. However, current methods suffer from

MLQENABLER: Enabling Secure Machine Learning Queries over Encrypted Database in Cloud Computing

arXiv:2607.08197v1 Announce Type: cross Abstract: In cloud computing, the public cloud service providers (CSPs) can provide cloud storage as the primary service while providing additional machine lear

MobiDiff: Semantic-Aware Multi-Channel Discrete Diffusion for Human Mobility Data Generation

arXiv:2607.08357v1 Announce Type: new Abstract: Human mobility data are essential for transportation optimization, urban planning, and resource allocation, yet real-world mobility data are costly to c

applicationsarxiv-cs-ai

Modular Pretraining Enables Access Control

arXiv:2607.08077v1 Announce Type: new Abstract: AI developers face a dual-use dilemma. An AI capability that helps one user cure a disease can help another synthesize one. This dilemma could be resolv

Monocular Vision Based Control Framework for Grasping

arXiv:2607.07897v1 Announce Type: new Abstract: Grasping in unstructured environments requires handling objects with widely different mechanical properties, from soft and deformable items to rigid eve

applicationsarxiv-cs-ro

MPFlow: Learning Budgeted Max-Flow Optimization on the Lightning Network with Deep Graph Reinforcement Learning

arXiv:2607.08703v1 Announce Type: new Abstract: We address liquidity placement in the Bitcoin Lightning Network (LN): given a fixed budget, which channels should a node open to maximize its routing ca

safetyarxiv-cs-lg

MSRNet: A Multi-Scale Recursive Network for Camouflaged Object Detection

arXiv:2511.12810v2 Announce Type: replace-cross Abstract: Camouflaged object detection is an emerging and challenging computer vision task that requires identifying and segmenting objects that blend s

Multi-agent Autoformalization of Tensor Network Theory

arXiv:2607.07857v1 Announce Type: cross Abstract: We build a team of specialized large language-model agents and present an agent-driven workflow for research-level formalization in theoretical physic

Multi-Agent Firewall Architecture for Privacy Protection of Sensitive Data in Interactions with Language Models

arXiv:2607.08282v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have become essential productivity tools, their integration into workflows without adequate safeguards creates sign

Multi-Distribution Robust Conformal Prediction

arXiv:2601.02998v2 Announce Type: replace Abstract: In many fairness and distribution robustness problems, one has access to labeled data from multiple source distributions yet the test data may come

safetyarxiv-cs-lg

Multi-Modal, Multi-Environment Machine Teaching for Robust Reward Learning

arXiv:2607.08647v1 Announce Type: cross Abstract: As autonomous agents are increasingly deployed across diverse operational contexts, aligning their behavior with human intent demands reward functions

Multi-Resolution Feature Stem for Diabetic Retinopathy lesion segmentation

model-releasesarxiv-cs-cv

arXiv:2607.08679v1 Announce Type: new Abstract: Diabetic Retinopathy (DR) is a leading cause of preventable blindness worldwide, requiring automated lesion segmentation using deep learning models for

MultiFair: Multimodal Balanced Fairness-Aware Medical Classification with Dual-Level Gradient Modulation

arXiv:2510.07328v2 Announce Type: replace-cross Abstract: Medical decision systems increasingly rely on data from multiple sources to ensure reliable and unbiased diagnosis. However, existing multimod

Multimodal 3D LUT Generation via StatLUT with Statistical Features for Photorealistic Style Transfer

arXiv:2607.08227v1 Announce Type: new Abstract: Photorealistic Style Transfer (PST) aims to transfer the color and tonal style of a reference to a content image while strictly preserving its structura

researcharxiv-cs-cv

Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks

arXiv:2607.07907v1 Announce Type: cross Abstract: With the growing adoption of VLMs, DMs, LLMs, and AFMs, these multimodal foundation models can inadvertently encode sensitive, copyrighted, biased, or

MulTTiPop: A Multitrack Transcription Dataset for Pop Music

arXiv:2607.08756v1 Announce Type: cross Abstract: We present MulTTiPop, a dataset of pop music segments and their associated multitrack MIDI recordings for the evaluation of automatic music transcript

MuScriptor: An Open Model for Multi-Instrument Music Transcription

arXiv:2607.08168v1 Announce Type: cross Abstract: Existing methods for automatic music transcription are often limited to single-instrument recordings or fail on complex, real music mixes. Although pr

applicationsarxiv-cs-lg

Native Video-Action Pretraining for Generalizable Robot Control

arXiv:2607.08639v1 Announce Type: cross Abstract: The advent of video-action models offers a promising path for robot control. Nevertheless, we argue that repurposing video generative models designed

safetyarxiv-cs-cv

Tutorials

Neural non-canonical Hamiltonian dynamics for long-time simulations

arXiv:2510.01788v2 Announce Type: replace Abstract: This work focuses on learning non-canonical Hamiltonian dynamics from data, where long-term predictions require the preservation of structure both i

tutorialsarxiv-cs-lg

NFTR: From Provable Mode-Averaging to Geodesic Subgoal Selection in Offline Goal-Conditioned RL

arXiv:2607.07855v1 Announce Type: new Abstract: Hierarchical Implicit Q-Learning (HIQL), an offline goal-conditioned RL method, selects subgoals by value-function advantages alone. This rule has two c

safetyarxiv-cs-lg

Nigeria Machinery: A Low-Resource Industrial Dataset with a Domain-Grounded Reasoning Layer

arXiv:2607.07883v1 Announce Type: new Abstract: There is relatively little, public, and model-ready data on industrial machinery for African economies. This makes it hard to do quantitative analysis o

applicationsarxiv-cs-ai

Omni-Sleep: A Sleep Foundation Model via Hierarchical Contrastive Learning of CNS--ANS Dynamic

arXiv:2607.07720v1 Announce Type: cross Abstract: Sleep physiology arises from the coordinated dynamics of the central nervous system (CNS) and autonomic nervous system (ANS), as reflected by multimod

researcharxiv-cs-ai

OmniFood-Bench: Evaluating VLMs for Nutrient Reasoning and Personalized Health Advice

arXiv:2607.08423v1 Announce Type: new Abstract: The rapid integration of Large Vision-Language Models (VLMs) into critical infrastructure promises to revolutionize personalized healthcare and dietary

Local Ai

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing

arXiv:2606.15920v2 Announce Type: replace Abstract: Reinforcement learning for multimodal large language models (MLLMs) is often hindered by severe reward sparsity in complex reasoning tasks. This cha

local-aiarxiv-cs-cv

On Exploring Input Resolution Scaling For Anytime LiDAR Object Detection

arXiv:2607.08391v1 Announce Type: cross Abstract: Making tradeoffs between execution latency and result utility (i.e., anytime computing) for adapting to dynamic operational requirements has been show

agentsarxiv-cs-lg

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting

arXiv:2607.08250v1 Announce Type: new Abstract: Dynamic scene reconstruction remains challenging due to the heterogeneous and spatially varying nature of real-world motion. Although recent 3D Gaussian

applicationsarxiv-cs-cv

On the Gradient Complexity of Private Optimization with Private Oracles

arXiv:2511.13999v2 Announce Type: replace Abstract: We study the running time, in terms of first order oracle queries, of differentially private empirical/population risk minimization of Lipschitz con

On the Role of Conversational Timing in Synthetic Training Data for ASR

arXiv:2607.08371v1 Announce Type: cross Abstract: Synthetic multi-speaker conversations are widely used to train conversational automatic speech recognition (ASR) systems, but it remains unclear which

Open-ended Multi-agent Autocurricula via Visual Inspection of Policies with Multi-modal LLMs

arXiv:2607.08193v1 Announce Type: cross Abstract: Open-ended curricula in Reinforcement Learning (RL) aim to train generally-capable agents by identifying tasks that facilitate learning increasingly c

Open-Vocabulary Object-Goal Navigation by Generalizing Semantic Mapping with Dense CLIP

arXiv:2407.09016v2 Announce Type: replace Abstract: Object-oriented embodied navigation tasks require agents to locate specific objects, either defined by category or images, in unseen environments. W

researcharxiv-cs-ro

OpenCoF: Learning to Reason Through Video Generation

arXiv:2607.08763v1 Announce Type: cross Abstract: Reasoning has become a core capability for large models, especially when reliable decisions require understanding logical consequences. Recent video g

researcharxiv-cs-ai

OPSD-V: On-Policy Self-Distillation for Post-Training Few-Step Autoregressive Video Generators

arXiv:2607.08766v1 Announce Type: new Abstract: We propose OPSD-V, an on-policy self-distillation paradigm for post-training few-step autoregressive (AR) video diffusion models. Existing few-step AR v

safetyarxiv-cs-cv

Tutorials

Optimal Learning Rate Scaling Depends on Data in Deep Scalar Linear Networks

arXiv:2607.07884v1 Announce Type: new Abstract: In this short note we consider the gradient descent dynamics of deep scalar linear networks, f(x) = prod_{l=1}^L w_l x, which enjoy exact time-course so

tutorialsarxiv-cs-lg

Out of Sight: Compression-Aware Content Protection against Agentic Crawlers

arXiv:2607.08180v1 Announce Type: cross Abstract: The rise of LLM-based agents with reasoning, summarization, and memory capabilities has created a new threat surface for online content that conventio

Overthinking: Amplifying Reasoning Weights to Extract Learned Secrets

arXiv:2607.08173v1 Announce Type: new Abstract: Black box auditing of language models is an essential pre-deployment tool, but it may miss subtle forms of misalignment and hidden information. To bette

researcharxiv-cs-ai

Local Ai

PARA-PV: Physics-Aware Retrieval-Augmented PV Prediction Based on Frozen Foundation Model and Distribution Shift Correction

arXiv:2607.08079v1 Announce Type: new Abstract: Accurate photovoltaic (PV) power forecasting is essential for reliable grid dispatch and renewable energy integration, yet it remains challenging becaus

local-aiarxiv-cs-ai

ParamMute: Suppressing Knowledge-Critical FFNs for Faithful Retrieval-Augmented Generation

arXiv:2502.15543v4 Announce Type: replace-cross Abstract: Large language models (LLMs) integrated with retrieval-augmented generation (RAG) have improved factuality by grounding outputs in external ev

Tutorials

Partial Causal Structure Learning for Valid Selective Conformal Inference under Interventions

arXiv:2603.02204v2 Announce Type: replace Abstract: Selective conformal prediction can yield substantially tighter uncertainty sets when we can identify calibration examples that are exchangeable with

tutorialsarxiv-cs-lg

path_boost: A Python Package for Interpretable Graph-Level Prediction using Path-Based Gradient Boosting

arXiv:2607.07935v1 Announce Type: cross Abstract: We present path_boost, a Python package for interpretable supervised learning on graph-structured input data. The package implements PathBoost, a grad

Persistent Multiscale Density-based Clustering

model-releasesarxiv-cs-lg

arXiv:2512.16558v3 Announce Type: replace Abstract: Clustering is a cornerstone of modern data analysis. Detecting clusters in exploratory data analyses (EDA) requires algorithms that make few assumpt

Persona Cartography: Charting Language Model Personality Traits in Weight Space

arXiv:2607.07916v1 Announce Type: new Abstract: Large language models exhibit recurring behavioural patterns -- personas -- that shape generalisation and safety, but we lack reliable tools for decompo