activity
20242026
most citedUni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts

3 citations · 10 across the 17 of their papers we have counts for

collaborators
Showing 2026Show all

5 papers · 1 filter

cs.CL2026

Hierarchical Acoustic-Semantic Modeling: Modality Separation and Semantic Coherence for Full-Duplex SLMs

Zhenyu Liu, Xuanyu Zhang, Yunxin Li +10

Developing seamless, high-performance, native intelligent full-duplex Spoken Language Models (SLMs) remains a critical challenge and long-standing goal for the speech and NLP commu…

cs.AI2026

DyCon: Dynamic Reasoning Control via Evolving Difficulty Modeling

Tengyao Tu, Yulin Li, Hui-Ling Zhen +6

Recent advances in Large Reasoning Models (LRMs) demonstrate remarkable performance improvements by iteratively reflecting, exploring, and executing complex tasks, yet suffer from…

cs.CL2026

CoCoReviewBench: A Completeness- and Correctness-Oriented Benchmark for AI Reviewers

Hexuan Deng, Xiaopeng Ke, Yichen Li +6

Despite the rapid development of AI reviewers, evaluating such systems remains challenging: metrics favor overlap with human reviews over correctness. However, since human reviews…

cs.MM2026

MSVBench: Towards Human-Level Evaluation of Multi-Shot Video Generation

Haoyuan Shi, Yunxin Li, Nanhao Deng +5

The evolution of video generation toward complex, multi-shot narratives has exposed a critical deficit in current evaluation methods. Existing benchmarks remain anchored to single-…

cs.CL2026

FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs

Qian Chen, Jinlan Fu, Changsong Li +3

Although Multimodal Large Language Models (MLLMs) demonstrate strong omni-modal perception, their ability to forecast future events from audio-visual cues remains largely unexplore…