Search: “multimodal”

DataSpace: Benchmarking Data Agents for Verifiable Analytics over Heterogeneous Workspaces

model-releasesarxiv-cs-ai

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

5 Aug 2026

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Does Forgetting Transfer Across Modalities? A Real-World Benchmark for Cross-Modal Knowledge Unlearning Evaluation

DGX agent

arXiv:2608.03791v1 Announce Type: new Abstract: Vision-Language Models (VLMs), like Large Language Models (LLMs), may memorize sensitive, copyrighted, or harmful knowledge from their pretraining corpo

model-releasesarxiv-cs-ai

5 Aug 2026

Toward Visual Grounding: A Survey

arXiv:2412.20206v4 Announce Type: replace Abstract: Visual Grounding, also known as Referring Expression Comprehension and Phrase Grounding, aims to ground the specific region(s) within the image(s) b

5 Aug 2026

Analyzing Speech Condition Effects in Dysarthric ASR: A Layer-wise Probing Study

arXiv:2608.01865v1 Announce Type: new Abstract: Automatic speech recognition (ASR) performance degrades sharply on dysarthric speech, yet how disordered articulation reshapes a model's internal repres

CAVE: Competence-Aware Visual Boundary Evidence Alignment for Video Temporal Grounding

arXiv:2608.02078v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have achieved substantial performance gains in Video Temporal Grounding (VTG) through reinforcement learning (RL).

safetyarxiv-cs-cl

Control Under Compression: Reliability Frontiers for Tool-Using Agents

arXiv:2608.01056v1 Announce Type: cross Abstract: Tool-using language-model agents are governed not only by task prompts but also by persistent system-side instructions that specify tools, arguments,

CrossProjection: Geometric Grounding Beyond Viewpoint Change in Architectural Drawings

arXiv:2608.00473v1 Announce Type: cross Abstract: Architectural drawings violate the usual assumption behind multi-view reasoning: plans and sections are cuts, while elevations are facade projections,

DocNavRAG: Document-Structured Graph RAG with Stateful Evidence Construction for Complex Document Question Answering

arXiv:2608.01565v1 Announce Type: new Abstract: Answering complex questions over large document collections requires assembling complementary evidence across sections and documents. GraphRAG offers st

agentsarxiv-cs-cl

Tutorials

Does Machine 'know' interpersonal pragmatics? Evidence from MARBERT's learning of emoji pragmatics in Arabic digital discourse

arXiv:2608.01174v1 Announce Type: new Abstract: This study examines Transformer-based models' ability to learn emoji pragmatics in Arabic digital discourse (ADD), providing evidence from MARBERT's beh

tutorialsarxiv-cs-cl

Expert-Choice Routing Enables Adaptive Computation in Diffusion Language Models

arXiv:2604.01622v2 Announce Type: replace-cross Abstract: Diffusion language models (DLMs) enable parallel, non-autoregressive text generation, yet existing DLM mixture-of-experts (MoE) models inherit

safetyarxiv-cs-cl

InteracVid: Building a Real Interactive Audio-Visual Response Dataset from Live-Chat Videos

arXiv:2608.01157v1 Announce Type: new Abstract: Large language models have made text the default medium for human--AI interaction, buttext alone cannot express the full range of responses required by

LLM generation novelty through the lens of semantic similarity

arXiv:2510.27313v3 Announce Type: replace-cross Abstract: Generation novelty is a key indicator of an LLM's ability to generalize, yet measuring it against full pretraining corpora is computationally

researcharxiv-cs-cl

Local Ai

LOCUS-DT: Localization via Observation-Conditioned Uncertainty Scoring with Digital Twins

arXiv:2608.00406v1 Announce Type: cross Abstract: Accurate indoor localization is essential for emerging applications in robotic navigation and search and rescue. While classical methods typically foc

local-aiarxiv-cs-lg

MMPhysVideo: Physically Plausible Video Generation Through Joint RGB-Perception Modeling

arXiv:2604.02817v2 Announce Type: replace Abstract: Despite advancements in generating visually stunning content, video diffusion models (VDMs) often yield physically inconsistent results due to pixel

safetyarxiv-cs-cv

Opt.Gear Technical Report

arXiv:2608.01034v1 Announce Type: new Abstract: We introduce Opt.Gear, a foundation model designed for efficient on-device deployment, real-tim inference, and strong task capability. It includes a den

RF-HOI: Recognize Human-Object Interaction with Radio Frequency Signals

arXiv:2608.00289v1 Announce Type: cross Abstract: Recognizing Human-Object Interactions (HOI) is essential for intelligent systems, underpinning applications in virtual and augmented reality, embodied

applicationsarxiv-cs-ro

RoMeRL: Balancing Feedback Coverage and the Memory-Reward Trap in Self-Evolving Agent Memory via Reduced-Order Utility States

arXiv:2608.02508v1 Announce Type: cross Abstract: Learning-based memory systems for self-evolving LLM agents face two tightly coupled challenges. First, trajectory-indexed utilities grow with the inte

agentsarxiv-cs-cl

SafeBuild-Bench: A Temporal-Robust Construction Safety Benchmark with Graph-Enhanced Data Mining

arXiv:2608.00068v1 Announce Type: new Abstract: Construction-safety models must handle concrete deployment risks, such as a worker standing near a scaffold edge without guardrails, rather than only re

Local Ai

SVRepair: Structured Visual Reasoning for Automated Program Repair

arXiv:2602.06090v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have recently been applied to Automated Program Repair (APR), yet most existing approaches remain unimodal and fa

local-aiarxiv-cs-cv

TIDES: A Longitudinal Bilingual Dataset for Modeling Multi-Party Social Dynamics

arXiv:2608.01724v1 Announce Type: new Abstract: Group conversations are fundamental to human collaboration, yet standard large language models (LLMs) still struggle with the complexities of multi-part

applicationsarxiv-cs-cl

Training-Free Out-of-Distribution Detection for Pathology Whole-Slide Images

arXiv:2608.01407v1 Announce Type: new Abstract: Safe deployment of AI methods in medicine requires robust guardrails that detect when input data deviate from the training distribution to ensure that m

Transformers perform adaptive partial pooling

arXiv:2602.03980v2 Announce Type: replace Abstract: Any language model must decide what to say in novel contexts based on information from similar contexts. But what about contexts that are not novel

researcharxiv-cs-cl

Trustworthiness Costs of Domain Adaptation in Small Language Models:A Cross-Architecture Empirical Study

arXiv:2608.00042v1 Announce Type: new Abstract: Domain adaptation of small language models (SLMs) has emerged as a practical strategy for deploying capable NLP systems in resource-constrained, high-st

When Words Divide: Diachronic Ideological Polarization in Political Discourse on Social Media

arXiv:2608.01176v1 Announce Type: new Abstract: Political polarization has become a defining feature of online discourse, yet its long-term evolution remains poorly understood. We present a longitudin

researcharxiv-cs-cl

XL-DocBench: Benchmarking Evidence-Grounded Extra-Long Document Understanding

arXiv:2608.00036v1 Announce Type: new Abstract: Real-world document tasks often ask professionals to answer questions from annual reports, regulations, clinical guidelines, and technical manuals that

Can LLMs Really Understand Item Difficulty Levels? Implications for Automated Item Generation Using LLMs

arXiv:2607.28634v1 Announce Type: new Abstract: The estimation of item difficulty plays a key role in both formative assessment and large-scale high-stakes summative assessments. This study explores h

ConnectED: A Curriculum-Aligned AI System for Vietnamese Instructional Lesson Planning and Student Learning

arXiv:2607.28647v1 Announce Type: cross Abstract: This paper presents ConnectED, a human-centered AI system that supports the full instructional lifecycle in Vietnamese education by linking curriculum

safetyarxiv-cs-ai

DragonCrawl: A Generative, Intent-Based Framework for Scalable Mobile End-to-End Testing

arXiv:2607.28750v1 Announce Type: cross Abstract: As mobile applications grow in complexity, traditional End-to-End (E2E) testing frameworks struggle with UI volatility, maintenance overhead, and cros

applicationsarxiv-cs-ai

Guarantees on Dynamical System Distinguishability for LLM Token Generation

arXiv:2607.28667v1 Announce Type: cross Abstract: Recent work has shown that classifying large language models (LLMs)' responses can be distinguished by modeling token embeddings as trajectories of a

researcharxiv-cs-ai

M3MAD-Bench: Multi-Dimensional Evaluation of Multi-Agent Debate Across Domains and Modalities

model-releasesarxiv-cs-ai

arXiv:2601.02854v2 Announce Type: replace Abstract: As an agent-level reasoning and coordination paradigm, Multi-Agent Debate (MAD) orchestrates multiple agents through structured debate to improve an

MerchantBench: Benchmarking LLM Agents for Long-Term Coherence in E-Commerce Operations

arXiv:2607.28956v1 Announce Type: new Abstract: Large language model agents are increasingly evaluated as autonomous tool users, yet most benchmarks focus on bounded tasks with immediate success crite

agentsarxiv-cs-ai

Tutorials

MoRAE: Flow-Friendly Self-Supervised Latents for Text-to-Motion Generation

arXiv:2607.29180v1 Announce Type: cross Abstract: Text-to-motion generation must produce motions that are semantically correct, temporally coherent, and physically plausible. A natural approach is to

tutorialsarxiv-cs-ai

The Formalism Trap: Are LLM-as-a-Judge Evaluators Blinded by Consensus Mimicry under Social Load?

arXiv:2607.28641v1 Announce Type: cross Abstract: We introduce the extit{Agentic Formalism Trap} and the Evaluative Dissonance Index (D_E), quantifying how LLM-as-a-Judge systems conflate structural p

agentsarxiv-cs-ai

Visual Distribution Anchoring for Efficient Prompt Tuning

arXiv:2607.28967v1 Announce Type: new Abstract: Prompt tuning adapts vision--language models with few trainable parameters, but existing approaches trade off efficiency and adaptation: static textual

Beyond Frame Selection: Generative Latent Evidence Aggregation for Long-Video Understanding

arXiv:2607.28516v1 Announce Type: new Abstract: Long-video understanding commonly compresses videos into a small set of frames or visual tokens for answer generation. Existing compact pipelines focus

Can LVLMs Uncover the Truth Behind Visual Illusions? An Analysis of Perceptual and Reasoning Capabilities

arXiv:2607.27747v1 Announce Type: new Abstract: Large Vision Language Models have integrated reasoning capabilities, elevating cognitive performance to new levels. However, existing evaluations either

EvoCause: LLM-Guided Evolution of Causal Graphs for Root Cause Analysis

model-releasesarxiv-cs-lg

arXiv:2607.27290v1 Announce Type: new Abstract: Modern telecommunication, cloud, and microservice systems emit correlated alarm cascades when components fail. Root cause analysis (RCA) aims to identif

Filling the Pareto-Optimal Front for Affordance Segmentation on Embedded Devices Using RGB-D Cameras

arXiv:2607.28293v1 Announce Type: new Abstract: While depth sensors have the potential to complement RGB data for affordance segmentation in wearable robots, their usage seems to remain underexplored.

applicationsarxiv-cs-cv

From Single- to Cross-Document: Benchmarking Multi-Granularity Event Analysis of Large Language Models

arXiv:2607.27654v1 Announce Type: new Abstract: Event analysis is an essential and fundamental direction of information extraction, involving various event-centric tasks at different granularity of do

Gradient-free Task-Conditioned Retrieval for On-Device In-Context Learning

arXiv:2607.27766v1 Announce Type: new Abstract: On-device in-context learning (ICL) relies on pre-inference retrieval to select demonstrations for useful context before downstream model inference. Thi

IDP AutoOpt: Agent-Driven Optimization of Document Processing Pipeline Configurations

model-releasesarxiv-cs-ai

arXiv:2607.26075v1 Announce Type: cross Abstract: We present IDP AutoOpt, an autonomous LLM agent that discovers high-performing configurations for intelligent document processing (IDP) pipelines. Tun

Inference-Time Agentic Decision Rules Beat Longer Evolving Search for Multi-Image Medical Reasoning

arXiv:2607.27564v1 Announce Type: new Abstract: Multi-image medical VQA is not merely a prompt-length problem; it is a fundamental challenge of agentic decision-making. Medical vision-language agents

safetyarxiv-cs-cv

Tutorials

Isolating to Harness: Cross-Division Distillation for Fully Unsupervised Anomaly Detection

arXiv:2508.18007v2 Announce Type: replace Abstract: Fully Unsupervised Anomaly Detection (FUAD) addresses the practical scenario where training data is contaminated with unlabeled anomalies. This sett

tutorialsarxiv-cs-cv

MedXplore: Towards Reliable and Unbiased Generalized Category Discovery in Medical Imaging

arXiv:2607.27620v1 Announce Type: new Abstract: Deep learning has shown strong potential in medical image analysis, but most existing methods rely on large-scale annotations and a closed-world assumpt

safetyarxiv-cs-cv

MUGEN: A Unified Framework for Efficient Motion Understanding and Generation

arXiv:2607.27581v1 Announce Type: new Abstract: Grounding human motion in language, and language in motion, is a central step toward physical AI systems that can understand, generate, and communicate

safetyarxiv-cs-lg

Negative controls reveal volume-driven confounding in radiomics and imaging foundation model features

arXiv:2607.28423v1 Announce Type: new Abstract: Radiomics and imaging foundation models promise non-invasive biomarkers of tumour biology, yet predictive signatures may reflect tumour volume or acquis

Objective-Aligned Direct Answer SFT for Robust Multi-Frame Medical VQA

arXiv:2607.27566v1 Announce Type: new Abstract: Multi-frame medical VQA appears to reward increasingly complex adaptation: controller-style inference, localization-aware reranking, static hard-negativ

OVEarth-Bench: Evaluating Category Breadth and Query Diversity for Open-Vocabulary Earth Observation

arXiv:2607.27278v1 Announce Type: new Abstract: Open-vocabulary Earth observation (EO) aims to localize geospatial concepts specified in natural language rather than a fixed label set. Existing benchm