Search: “models”

GUARD: Grounding Uncertainty and Ablation-Based Risk Detection for Diffusion-Based VLAs

arXiv:2608.04510v1 Announce Type: cross Abstract: Diffusion-based vision-language-action (VLA) policies can generate plausible actions even when their predictions are weakly grounded in the visual and

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Industrial Synthetic Segment Pre-training

DGX agent

arXiv:2505.13099v3 Announce Type: replace Abstract: Vision Foundation Models (VFMs) have made remarkable progress and are increasingly being applied to segmentation tasks in real-world industrial sett

applicationsarxiv-cs-cv

6 Aug 2026

Label-Free Target-Domain Adaptation for Unconstrained Event-Image Feature Matching via Dual-Stage Distillation

arXiv:2607.10082v2 Announce Type: replace Abstract: Building pixel-level correspondence between event and image data is a fundamental task for multi-sensor systems. However, existing cross-modal match

Lindblad-Inspired Multi-Timescale Reservoir Computing with Separable Rotation and Dissipation

arXiv:2608.04028v1 Announce Type: cross Abstract: Echo-state networks enable efficient temporal learning by fixing the recurrent dynamics and training only a linear readout. However, conventional rese

Mimir: A Neuro-Symbolic Memory System with Dynamic Grounding for Embodied Agents in Interactive Environments

model-releasesarxiv-cs-ro

arXiv:2608.04933v1 Announce Type: new Abstract: Long-horizon embodied task requires agents to act under partial observability while preserving both scene belief and execution progress. Flat histories

Modality Agreement- and Conflict-Aware Prototype Hypergraph Learning for Multimodal Intent Understanding

arXiv:2608.04054v1 Announce Type: cross Abstract: Multimodal intent recognition requires understanding not only what textual, acoustic, and visual signals share, but also how they disagree. Such disag

Multi-Objective Ranking for Live-Streaming: Balancing Fresh and Delayed Signals with Segment-Aware Targeting

arXiv:2608.04455v1 Announce Type: cross Abstract: One of the most challenging problems entertainment live-streaming services face in recommendation systems is that user behaviors are sparse and delaye

safetyarxiv-cs-lg

muSync-GS: Physics-Synchronized Driving Video Synthesis for Weather and Geometric Road Hazards

arXiv:2608.04412v1 Announce Type: new Abstract: High-quality driving data are essential for autonomous-driving systems and generative world models. However, rare and safety-critical scenarios involvin

safetyarxiv-cs-cv

OmniVR: Joint Video-Audio Conditional Generation for Restoring Degraded Historical Films

arXiv:2608.04224v1 Announce Type: new Abstract: Historical films suffer from co-occurring visual and audio degradations---blur, noise, flicker, hiss, clipping, and dropout---yet existing methods resto

Research

Recurrent Residual Quantization: A Progressive Multi-Precision Representation for LLMs

arXiv:2608.04048v1 Announce Type: cross Abstract: Serving large language models (LLMs) under diverse deployment constraints requires flexible trade-offs between accuracy, memory footprint, and through

researcharxiv-cs-ai

Relevant but Incomplete: Referential Dangling as a Paradigm-Level Failure Mode in Hard Prompt Compression

arXiv:2608.04569v1 Announce Type: new Abstract: Hard prompt compression reduces long-context inference cost by independently scoring tokens, sentences, or chunks and retaining the highest-scoring unit

Retrieve in Time, Correct in Frequency

model-releasesarxiv-cs-ro

arXiv:2608.04527v1 Announce Type: new Abstract: Frozen vision-language-action (VLA) policies generate temporally extended action chunks, but long-horizon manipulation remains vulnerable to accumulated

Robust and Efficient Motion Reasoning for Privacy-Aware Classroom Incident Recognition

arXiv:2608.05115v1 Announce Type: cross Abstract: Can computer vision help make classrooms safer? In this pilot study, we investigate privacy-aware and computationally efficient classroom incident rec

Robustness Emerges Early in Training Dynamics, but Is Not Preserved

arXiv:2608.04442v1 Announce Type: cross Abstract: Robustness to natural corruptions remains a fundamental challenge for deep neural networks. In this paper, we identify a robustness fading phenomenon

SimMOF: AI agent for Automated MOF Simulations

arXiv:2603.29152v2 Announce Type: replace Abstract: Metal-organic frameworks (MOFs) offer a vast design space, and as such, computational simulations play a critical role in predicting their structura

SmartMage: Dynamic Modality Orchestration for 3D Scene Understanding

arXiv:2608.05137v1 Announce Type: new Abstract: Understanding 3D scenes is fundamental to embodied intelligence, requiring joint reasoning over heterogeneous information from multiple modalities, incl

SpecRoll: Fast-Slow Verifier-Feedback Adaptation for Speculative Reinforcement Learning Rollouts

arXiv:2608.04962v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training improves the reasoning capabilities of large language models, but autoregressive rollout generation remains

safetyarxiv-cs-cl

Strategic Evaluation of Planning Strategies for LLM Agents in Cyber-Physical Systems

arXiv:2608.04265v1 Announce Type: cross Abstract: Evaluations of LLM planning agents largely ask whether a task succeeds or a declared plan is followed. In strategic cyber-physical systems, a stronger

Agents

stratum: A System Infrastructure for Massive Agent-Centric ML Workloads

arXiv:2603.03589v3 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) transform how machine learning (ML) pipelines are developed and evaluated. LLMs enable a new t

agentsarxiv-cs-lg

STRIVE: Probing Reasoning Limits in Graded Plausibility Generation and Evaluation

arXiv:2608.04567v1 Announce Type: new Abstract: Event knowledge concerns who does what to whom. Psycholinguists use event-plausibility judgments to examine how this knowledge supports human language p

Local Ai

Teaching MLLMs to Say No: Generalized Referring Expression Comprehension via Refusal Calibrated GRPO

arXiv:2608.04698v1 Announce Type: cross Abstract: We tackle the challenging yet underexplored task of Generalized Referring Expression Comprehension (GREC), which requires a model to localize the obje

local-aiarxiv-cs-ai

The Yokai Learning Environment: Tracking Beliefs Over Space and Time

arXiv:2508.12480v3 Announce Type: replace Abstract: The ability to cooperate with unknown partners is a central challenge in cooperative AI and widely studied in the form of zero-shot coordination (ZS

TIDE: A Physically Diverse 3D Turbulence Benchmark Dataset for Advancing Scientific Machine Learning

model-releasesarxiv-cs-lg

arXiv:2608.04222v1 Announce Type: cross Abstract: Turbulence is a central testbed for machine learning on physical dynamics because its governing laws are known exactly. However, most existing studies

Towards Physics of Multimodal Pretraining: Knowledge Flow, Modality Synergy, Early Unification, and Recipes

arXiv:2608.05000v1 Announce Type: new Abstract: Vision offers a critical axis for advancing foundation models, driving a shift towards natively unified multimodal pretraining. Despite this momentum, t

safetyarxiv-cs-cv

Local Ai

Trace, Verify, and Correct: A Training-Free Framework for Spatial Reasoning in Multimodal LLMs

arXiv:2608.04759v1 Announce Type: cross Abstract: Although Multimodal Large Language Models (MLLMs) have made substantial progress, their spatial reasoning may still produce intermediate judgments inc

local-aiarxiv-cs-cl

Tropical Algebraic Geometry for Neuronal Representations: An Arakelov-Green Measure Based Descriptor for Graph Learning

arXiv:2608.04460v1 Announce Type: cross Abstract: The quantitative analysis of 3D neuronal morphologies requires capturing both graph topology and spatial geometry. Current message-passing Graph Neura

Two-Level Meta-Rubrics for Evaluating Open-Ended Generation: GAMUT, a Benchmark for Factual Completeness

arXiv:2607.19322v2 Announce Type: replace Abstract: Rubric-based evaluation of open-ended generation faces a fundamental tension between expressiveness and reliability. Authoring a faithful rubric req

UG-UMRE: Uncertainty-Guided Modality Augmentation and Distributional Calibration for Unified Multimodal Relation Extraction

arXiv:2608.04949v1 Announce Type: cross Abstract: Unified Multimodal Relation Extraction (UMRE) aims to identify intra-modal and cross-modal relations between textual entities and visual objects. Howe

Visual Representation Matters: Exploiting Temporal Differences in Video-to-Audio Generation

arXiv:2608.04902v1 Announce Type: new Abstract: Video-to-audio (V2A) generation extends image-to-audio generation (I2A) by introducing consecutive frames that provide essential temporal cues for audio

Zero-shot reasoning for simulating scholarly peer-review

arXiv:2510.02027v2 Announce Type: replace Abstract: Scholarly publishing requires scalable scrutiny supported by auditable evidence. This paper presents a two-component benchmark of xPeer, the peer-re

3DGSI-Assessor: A Large-Scale Dataset and An LMM-based Method for 3D Gaussian Splatting Image Quality Assessment

arXiv:2608.03279v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has become a dominant representation for real-time novel view synthesis (NVS), yet its storage footprint makes compression

Hardware

A Deployment-Friendly Foundational Framework for Efficient Computational Pathology

arXiv:2602.14010v2 Announce Type: replace-cross Abstract: Pathology foundation models (PFMs) generalize well across computational pathology tasks but remain costly for gigapixel whole-slide image anal

hardwarearxiv-cs-ai

Hardware

AcceptMoE: Commitment-Weighted Self-Sizing Verifier Expert Sets for Efficient MoE Speculative Decoding

arXiv:2608.02989v1 Announce Type: cross Abstract: Speculative decoding verifies a tree of draft tokens in one target-model forward pass. For a mixture-of-experts (MoE) target, however, parallel verifi

hardwarearxiv-cs-cl

Research

Adversarial Purification by Consistency-aware Latent Space Optimization on Data Manifolds

arXiv:2412.08394v2 Announce Type: replace Abstract: Deep neural networks (DNNs) are vulnerable to adversarial samples crafted by adding imperceptible perturbations to clean data, potentially leading t

researcharxiv-cs-lg

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation

arXiv:2608.03166v1 Announce Type: new Abstract: Role-Playing Language Agents (RPLAs) are increasingly deployed in high-stakes applications such as healthcare assistance, customer support, and educatio

Aligned in Form, Not in Meaning: The Comprehension - Containment Decoupling of LLM Safety in Low-Resource Bangla Derogatory Speech

arXiv:2608.02941v1 Announce Type: new Abstract: We audit five frontier large language models on native Bangla derogatory speech (gali) across six protocols to test a single hypothesis: Comprehension-C

safetyarxiv-cs-cl

Amortized Interventional Forecasting for Multivariate CIR Processes

arXiv:2608.03715v1 Announce Type: new Abstract: Mean-reverting dynamics are pervasive in finance, and the Cox--Ingersoll--Ross (CIR) process is a standard model for the time series they produce, from

applicationsarxiv-cs-lg

ATFlash: Per-RoPE-Wavelength Attention Windows for Compute/Memory-Efficient LLM Inference

arXiv:2608.02947v1 Announce Type: cross Abstract: The attention score with rotary position embeddings (RoPE) decomposes exactly into a sum over its 2D-rotation frequency pairs, and each pair's wavelen

BBOWP-Bench: Evaluating LLMs on Black-Box Optimization Word Problems

arXiv:2608.02612v1 Announce Type: new Abstract: Formulating an optimization problem strongly affects the quality of the final solution, yet good formulations usually require substantial expertise. Rec

Beyond Either-Or Reasoning: Transduction and Induction as Cooperative Problem-Solving Paradigms

arXiv:2505.14744v3 Announce Type: replace-cross Abstract: Traditionally, in Programming-by-example (PBE) the goal is to synthesize a program from a small set of input-output examples. Lately, PBE has

CADET: Physics-Grounded Causal Auditing and Training-Free Deconfounding of End-to-End Driving Planners

arXiv:2606.14438v3 Announce Type: replace-cross Abstract: End-to-end (E2E) autonomous-driving planners trained by imitation are prone to statistical shortcuts: they associate scene elements that merel

Channel-wise Dynamic Knowledge Distillation via Adaptive Sample Generation for Action Recognition

arXiv:2608.03100v1 Announce Type: new Abstract: Knowledge Distillation (KD) offers a promising yet underexplored path for compressing large action recognition models. However, existing KD methods suff

safetyarxiv-cs-cv

Agents

ContinualSkillBench: Can LLM Agents Truly Evolve Their Capabilities?

arXiv:2608.03874v1 Announce Type: new Abstract: Modern agent frameworks equip large language models with external skill libraries to solve complex tasks. However, it remains unclear whether these syst

agentsarxiv-cs-ai

Cross-Country Learning for National Infectious Disease Forecasting Using European Data

arXiv:2601.20771v2 Announce Type: replace-cross Abstract: Accurate forecasting of infectious disease incidence is critical for public health planning and timely intervention. While most data-driven fo

applicationsarxiv-cs-lg

CURV: Enhancing Chart Understanding Through Curriculum Visual Grounded Reasoning

arXiv:2608.02833v1 Announce Type: cross Abstract: Chart question answering (CQA) requires multimodal large language models (MLLMs) to integrate visual comprehension with logical reasoning, yet current

applicationsarxiv-cs-ai

CVPO: Enhancing LLM Reinforcement Learning Reasoning via Value-Variance Adaptation and Dynamic Curriculum Learning

arXiv:2608.03068v1 Announce Type: cross Abstract: Reinforcement learning (RL) has emerged as an effective method for enhancing the reasoning capabilities of large language models (LLMs). However, exis

safetyarxiv-cs-ai

DAIF: A Data-Driven Intermediate Fusion Framework for Multimodal Supervised Learning via Approximate Message Passing

model-releasesarxiv-cs-lg

arXiv:2608.02769v1 Announce Type: cross Abstract: Multimodal supervised learning seeks to leverage multiple heterogeneous data sources to improve predictive performance. A central challenge is determi

DataSpace: Benchmarking Data Agents for Verifiable Analytics over Heterogeneous Workspaces

arXiv:2608.03451v1 Announce Type: new Abstract: Data agents enable natural-language analytics over organizational workspaces, where relevant evidence may be scattered across databases, structured file