activity
20242026
most citedAIM 2024 Challenge on Video Super-Resolution Quality Assessment: Methods and Results

7 citations · 26 across the 58 of their papers we have counts for

collaborators

69 papers

eess.AS2026

PW-Pruning: Phase-Aware Expert Selection for Speech-Centric Omni-Modal Models

Junjie Cao, Fengping Tian, Wenjie Zhou +5

Sparse routing reduces per-token computation but leaves the full expert bank resident in memory. We study expert pruning for speech-centric omni-modal models, where pooling calibra…

cs.CV2026

TextVerifier: Seeing Beyond Recognition to Verify Chinese Text Rendering

Yiyang Chen, Guo-Hua Wang, Yaoli Liu +4

Text-to-image models increasingly generate readable Chinese text that still contains local rendering defects, such as a character with an extra or missing stroke or a malformed com…

cs.CV2026

Efficient Scene-Text Refinement via Pixel-Space Grouped Image Generation

Yaoli Liu, Guo-Hua Wang, Yiyang Chen +4

Generated images often have coherent layouts and visual content, yet local errors in small text and complex characters still limit their readability and practical use. Scene-text r…

cs.CV2026

MVAgent: Multi-Agent Video Generation via Consistent Condition Construction and Shot-Level Policy Optimization

Xiangyu Kong, Wenjie Zhou, Fengping Tian +5

Multi-shot agentic video generation requires consistent character appearance, stable spatial layout across camera angles, and continuous character state between shots. When every s…

cs.AI2026

CHIME: Credit-Aware Hierarchical Memory Evolution for Long-Horizon Agentic Planning

Yongshi Ye, Tian Lan, Feihu Jiang +7

Planning is a central capability that enables agents to decompose complex long-horizon tasks into manageable steps. Test-time search and training-based methods improve planning but…

cs.CL2026

WnW: Waxing-and-Waning KV Cache for Long-Form Speech LLMs

Yiming Yao, Chenyang Lyu, Xuanfan Ni +4

Long-form audio inputs make the KV cache the dominant memory cost of speech LLMs. Prefill-only KV compression methods permanently discard audio KV positions once evicted, with no p…

cs.AI2026

Search2Skill: Skill Distillation Beyond Knowledge Boundaries Via Rubric-Based Reinforcement Learning

Muyang Ye, Tian Lan, Feihu Jiang +10

Reusable skills, which encapsulate the procedural knowledge required to solve real-world professional tasks, offer LLM-based agents a path toward self-evolution in expert domains.…

cs.CV2026

OvisOCR2 Technical Report

Shiyin Lu, Yinglun Li, Yu Xia +10

We introduce OvisOCR2, a 0.8B document parsing model. OvisOCR2 is designed as an end-to-end parser: given a document page image, it generates a Markdown representation in natural r…

cs.CL2026

VIDA: A Dataset for Visually Dependent Ambiguity in Multimodal Machine Translation

Jingheng Pan, Xintong Wang, Longyue Wang +3

Ambiguity resolution is a key challenge in multimodal machine translation (MMT), where models must genuinely leverage visual input to map an ambiguous expression to its intended me…

cs.CL2026

CulturALL: Benchmarking Multilingual and Multicultural Competence of LLMs on Grounded Tasks

Peiqin Lin, Chenyang Lyu, Wenjiang Luo +22

Large language models (LLMs) are now deployed worldwide, inspiring a surge of benchmarks that measure their multilingual and multicultural abilities. However, these benchmarks prio…

cs.CL2026

Incentivizing Parametric Knowledge via Reinforcement Learning with Verifiable Rewards for Cross-Cultural Entity Translation

Jiang Zhou, Xiaohu Zhao, Xinwei Wu +8

Cross-cultural entity translation remains challenging for large language models (LLMs) as literal or phonetic renderings are usually yielded instead of culturally appropriate trans…

cs.CV2026

Walk the Talk: Bridging the Reasoning-Action Gap for Thinking with Images via Multimodal Agentic Policy Optimization

Wenhao Yang, Yu Xia, Jinlong Huang +10

Recent advancements in Multimodal Large Language Models (MLLMs) have incentivized models to ``think with images'' by actively invoking visual tools during multi-turn reasoning. The…

cs.CL2026

Marco DeepResearch: Unlocking Efficient Deep Research Agents via Verification-Centric Design

Bin Zhu, Qianghuai Jia, Tian Lan +6

Deep research agents autonomously conduct open-ended investigations, integrating complex information retrieval with multi-step reasoning across diverse sources to solve real-world…

cs.AI2026

Building Autonomous GUI Navigation via Agentic-Q Estimation and Step-Wise Policy Optimization

Yibo Wang, Guangda Huzhang, Yuwei Hu +7

Recent advances in Multimodal Large Language Models (MLLMs) have substantially driven the progress of autonomous agents for Graphical User Interface (GUI). Nevertheless, in real-wo…

cs.CL2026

UMEM: Unified Memory Extraction and Management Framework for Generalizable Memory

Yongshi Ye, Hui Jiang, Feihu Jiang +7

Self-evolving memory serves as the trainable parameters for Large Language Models (LLMs)-based agents, where extraction (distilling insights from experience) and management (updati…

cs.CL2026

Table-as-Search: Formulate Long-Horizon Agentic Information Seeking as Table Completion

Tian Lan, Felix Henry, Bin Zhu +7

Current Information Seeking (InfoSeeking) agents struggle to maintain focus and coherence during long-horizon exploration, as tracking search states, including planning procedure a…

cs.AI2026

Difficulty-Estimated Policy Optimization

Yu Zhao, Fan Jiang, Tianle Liu +4

Recent advancements in Large Reasoning Models (LRMs), exemplified by DeepSeek-R1, have underscored the potential of scaling inference-time compute through Group Relative Policy Opt…

cs.SD2026

Speech-XL: Towards Long-Form Speech Understanding in Large Speech Language Models

Haoqin Sun, Chenyang Lyu, Shiwan Zhao +5

Despite the growing success of Large Speech Language Models (LSLMs) in processing short-term acoustic signals, their extension to long-form audio understanding is severely bottlene…

cs.AI2026

A State-Transition Framework for Efficient LLM Reasoning

Liang Zhang, Yu Zhao, Longyue Wang +4

While Long Chain-of-Thought (CoT) reasoning significantly improves Large Language Models (LLMs) performance on complex reasoning tasks, the substantial computational and memory cos…

cs.CV2026

Vectra: A New Metric, Dataset, and Model for Visual Quality Assessment in E-Commerce In-Image Machine Translation

Qingyu Wu, Yuxuan Han, Haijun Li +5

In-Image Machine Translation (IIMT) powers cross-border e-commerce product listings; existing research focuses on machine translation evaluation, while visual rendering quality is…

cs.SD2026

LongSpeech: A Scalable Benchmark for Transcription, Translation and Understanding in Long Speech

Fei Yang, Xuanfan Ni, Renyi Yang +7

Recent advances in audio-language models have demonstrated remarkable success on short, segment-level speech tasks. However, real-world applications such as meeting transcription,…

cs.CL2026

Finding the Translation Switch: Discovering and Exploiting the Task-Initiation Features in LLMs

Xinwei Wu, Heng Liu, Xiaohu Zhao +6

Large Language Models (LLMs) frequently exhibit strong translation abilities, even without task-specific fine-tuning. However, the internal mechanisms governing this innate capabil…

cs.CL2026

Triplets Better Than Pairs: Towards Stable and Effective Self-Play Fine-Tuning for LLMs

Yibo Wang, Hai-Long Sun, Qing-Guo Chen +4

Recently, self-play fine-tuning (SPIN) has been proposed to adapt large language models to downstream applications with scarce expert-annotated data, by iteratively generating synt…

cs.CL2026

Can LLMs Track Their Output Length? A Dynamic Feedback Mechanism for Precise Length Regulation

Meiman Xiao, Ante Wang, Qingguo Hu +5

Precisely controlling the length of generated text is a common requirement in real-world applications. However, despite significant advancements in following human instructions, La…