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20172026
most citedCompact Descriptors for Video Analysis: the Emerging MPEG Standard

7 citations · 27 across the 29 of their papers we have counts for

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Showing 2026Show all

19 papers · 1 filter

cs.SE2026

ProductWebBench: Evaluating Website Continuity Beyond Task Completion

Jiajun Wu, Jian Yang, Yaxin Du +9

Frontend coding agents are usually graded on one question: did the requested target get built. Real engineering changes carry a second obligation, because the rest of the site has…

cs.CV2026

HiRAE: Hierarchical Representation Autoencoding with Residual Budgets

Xuanyu Zhu, Yan Bai, Yang Shi +5

Pretrained visual representations support image generation, but may not fully preserve the fine-grained details needed for faithful reconstruction. Meanwhile, intermediate encoder…

cs.CV2026

TUE-Detector: A Tool-Using Expert MLLM-Based Detector for AI-Generated Videos

Yichen Wu, Haoxuan Qu, Yongxing Dai +5

AI-generated video detection, which aims to distinguish AI-generated videos from real ones, has recently received increasing research attention. To perform this task reliably, a ke…

cs.CV2026

CANVAS: Consistency-Aware Navigation via Visual Adaptive Sampling for Long-Context Text-to-SVG Generation

Yichen Wu, Haoxuan Qu, Yihang Lou +2

Autoregressive large models have recently advanced Text-to-SVG generation from simple icons to complex, long-context graphics, yet standard autoregressive decoding often fails to m…

cs.AI2026

StainFlow: Entity-Stain Tracking and Evidence Linking for Process Rewards in GUI Agents

Haojie Hao, Longkun Hao, Yihang Lou +8

Reinforcement Learning (RL) has become a promising approach for improving GUI Agents in long-horizon, stochastic digital environments, but trajectory-level success feedback is too…

cs.AI2026

MIRAGE: Mobile Agents with Implicit Reasoning and Generative World Models

Zhichao Yang, Yuanze Hu, Haojie Hao +7

Mobile agents are increasingly expected to operate everyday applications from screenshots and language goals, where reliable control requires reasoning over screen affordances, mul…

cs.CL2026

Mechanistic Insights into Functional Sparsity in Multimodal LLMs via CoRe Heads

Ruoxi Sun, Quantong Qiu, Juntao Li +3

While Multimodal Large Language Models (MLLMs) demonstrate remarkable proficiency on complex vision-language tasks, the mechanisms by which they extract query-relevant visual featu…

cs.LG2026

Speculative Rollback Correction for Quality-Diverse Web Agent Imitation

Longkun Hao, Hongyu Lin, Hao Li +11

Training interactive web agents through imitation learning from expert trajectories has emerged as a highly effective approach. However, determining the optimal timing for expert i…

cs.CV2026

ToolFG: Towards Well-Grounded Fine-Grained Image Classification

Yu Xue, Haoxuan Qu, Zhuoling Li +4

Fine-grained image classification (FGIC) has broad applications and has attracted significant research attention. In this paper, we explore a novel paradigm for solving FGIC by pro…

cs.SE2026

HTMLCure: Turning Browser Experience into State Guided Repair for Interactive HTML

Jiajun Wu, Jian Yang, Tuney Zheng +4

LLMs can now produce full HTML pages, but many of those pages are only superficially correct: they render once, then fail under scroll, hover, click, resize, or gameplay. Evaluatio…

cs.SE2026

A Case for Agentic Tuning: From Documentation to Action in PostgreSQL

Hongyu Lin, Mingyu Li, Weichen Zhang +4

Documentation has long guided computer system tuning by distilling expert knowledge into per-parameter recommendations. Yet such guides capture only what experts conclude, discardi…

cs.CV2026

OmniSelect: Dynamic Modality-Aware Token Compression for Efficient Omni-modal Large Language Models

Morunliu Yang, Ruotao Xu, Le Li +6

Omnimodal large language models (OmniLLMs) have recently gained increasing attention for unified audio-video understanding. However, processing long multimodal token sequences intr…

cs.CV2026

Beyond the Last Layer: Multi-Layer Representation Fusion for Visual Tokenization

Xuanyu Zhu, Yan Bai, Yang Shi +4

Representation autoencoders that reuse frozen pretrained vision encoders as visual tokenizers have achieved strong reconstruction and generation quality. However, existing methods…

cs.CV2026

MMVIAD: Multi-view Multi-task Video Understanding for Industrial Anomaly Detection

Xiran Zhao, Jing Jin, Yan Bai +6

Industrial anomaly detection is critical for manufacturing quality control, yet existing datasets mainly focus on static images or sparse views, which do not fully reflect continuo…

cs.CL2026

MemReread: Enhancing Agentic Long-Context Reasoning via Memory-Guided Rereading

Baibei Ji, Xiaoyang Weng, Juntao Li +3

Long-context reasoning tasks have motivated agent-memory approaches that process document chunks sequentially while maintaining a dynamically updated memory, avoiding the quadratic…

cs.CV2026

Unveiling Fine-Grained Visual Traces: Evaluating Multimodal Interleaved Reasoning Chains in Multimodal STEM Tasks

Jing Jin, Hao Liu, Yan Bai +9

Multimodal large language models (MLLMs) have shown promising reasoning abilities, yet evaluating their performance in specialized domains remains challenging. STEM reasoning is a…

cs.CL2026

Learning to Edit Knowledge via Instruction-based Chain-of-Thought Prompting

Jinhu Fu, Yan Bai, Longzhu He +4

Large language models (LLMs) can effectively handle outdated information through knowledge editing. However, current approaches face two key limitations: (I) Poor generalization: M…

cs.CV2026

Diagnosing and Repairing Unsafe Channels in Vision-Language Models via Causal Discovery and Dual-Modal Safety Subspace Projection

Jinhu Fu, Yihang Lou, Qingyi Si +3

Large Vision-Language Models (LVLMs) have achieved impressive performance across multimodal understanding and reasoning tasks, yet their internal safety mechanisms remain opaque an…

cs.AI2026

VTC-Bench: Evaluating Agentic Multimodal Models via Compositional Visual Tool Chaining

Xuanyu Zhu, Yuhao Dong, Rundong Wang +9

Recent advancements extend Multimodal Large Language Models (MLLMs) beyond standard visual question answering to utilizing external tools for advanced visual tasks. Despite this pr…