4 citations · 7 across the 6 of their papers we have counts for
8 papers
RoPE at the End of Its Rope? Theory, Diagnosis, and Mitigation of Long-Context Failures
Yuyang Wu, Yufeng Du, Hao Peng
Long-context failures of RoPE-based language models can arise from RoPE's intrinsic tradeoff between maintaining stable token preferences and distinguishing nearby positions. Deter…
NBA_Streaming: A Large-Scale Benchmark for Fine-Grained Basketball Commentary Generation in Continuous Streams
Lifang Wu, Yuyang Wu, Yangdong Gao +3
Live basketball commentary generation requires determining when an event is sufficiently observable and describing it before subsequent events unfold. However, existing methods are…
ReactBench: A Cause-Driven Benchmark for Multimodal Hallucination via Systematic Evaluation
Shizhe Zhou, Bohan Jia, Kai Wu +4
While multimodal large language models (MLLMs) have achieved rapid progress in vision-language understanding, they remain prone to multimodal hallucinations, producing responses th…
Bridging Visual Representation and Reinforcement Learning from Verifiable Rewards in Large Vision-Language Models
Yuhang Han, Yuyang Wu, Zhengbo Jiao +6
Reinforcement Learning from Verifiable Rewards (RLVR) has substantially enhanced the reasoning capabilities of large language models in abstract reasoning tasks. However, its appli…
OpenMic: A Multi-Agent-Based Stand-Up Comedy Generation System
Yuyang Wu, Hanzhong Cao, Jianhao Chen +1
Chinese stand-up comedy generation goes beyond plain text generation, requiring culturally grounded humor, precise timing, stage-performance cues, and implicit multi-step reasoning…
Momentum Posterior Regularization for Multi-hop Dense Retrieval
Zehua Xia, Yuyang Wu, Yiyun Xia +1
Multi-hop question answering (QA) often requires sequential retrieval (multi-hop retrieval), where each hop retrieves missing knowledge based on information from previous hops. To…
When More is Less: Understanding Chain-of-Thought Length in LLMs
Yuyang Wu, Yifei Wang, Ziyu Ye +3
Large Language Models (LLMs) employ Chain-of-Thought (CoT) reasoning to deconstruct complex problems. While longer CoTs are often presumed superior, this paper challenges that noti…
A Theoretical Understanding of Self-Correction through In-context Alignment
Yifei Wang, Yuyang Wu, Zeming Wei +2
Going beyond mimicking limited human experiences, recent studies show initial evidence that, like humans, large language models (LLMs) are capable of improving their abilities pure…