1 citations · 1 across the 5 of their papers we have counts for
6 papers
From Candidate Tokens to Final Outcomes: Decoding Relative Long-Horizon Candidate Value from Reasoning Model Representations
Yixin Yang, Yue Wang, Fandong Meng +1
Large reasoning models generate reasoning trajectories token by token. At a given prefix, multiple next-token candidates may be plausible, yet shape subsequent reasoning and differ…
Decoding in Geometry: Alleviating Embedding-Space Crowding for Complex Reasoning
Yixin Yang, Qingxiu Dong, Zhifang Sui
Sampling-based decoding underlies complex reasoning in large language models (LLMs), where decoding strategies critically shape model behavior. Temperature- and truncation-based me…
RICo: Refined In-Context Contribution for Automatic Instruction-Tuning Data Selection
Yixin Yang, Qingxiu Dong, Linli Yao +2
Data selection for instruction tuning is crucial for improving the performance of large language models (LLMs) while reducing training costs. In this paper, we propose Refined Cont…
SCoRE: Benchmarking Long-Chain Reasoning in Commonsense Scenarios
Weidong Zhan, Yue Wang, Nan Hu +12
Currently, long-chain reasoning remains a key challenge for large language models (LLMs) because natural texts lack sufficient explicit reasoning data. However, existing benchmarks…
Beyond Single Frames: Can LMMs Comprehend Temporal and Contextual Narratives in Image Sequences?
Xiaochen Wang, Heming Xia, Jialin Song +9
Large Multimodal Models (LMMs) have achieved remarkable success across various visual-language tasks. However, existing benchmarks predominantly focus on single-image understanding…
Can Large Multimodal Models Uncover Deep Semantics Behind Images?
Yixin Yang, Zheng Li, Qingxiu Dong +2
Understanding the deep semantics of images is essential in the era dominated by social media. However, current research works primarily on the superficial description of images, re…