1 citations · 1 across the 5 of their papers we have counts for
5 papers
To Reason or to Fabricate: Reasoning Without Shortcuts via Hint-Anchored Pairwise Aggregation
Jiuheng Lin, Chen Zhang, Yansong Feng
While reinforcement learning (RL) significantly enhances LLM reasoning, its efficacy is severely undermined by Pre-RL data overlap, where RL datasets overlap with pretraining or SF…
EVPO: Explained Variance Policy Optimization for Adaptive Critic Utilization in LLM Post-Training
Chengjun Pan, Shichun Liu, Jiahang Lin +10
Reinforcement learning (RL) for LLM post-training faces a fundamental design choice: whether to use a learned critic as a baseline for policy optimization. Classical theory favors…
Efficient Low-Resource Language Adaptation via Multi-Source Dynamic Logit Fusion
Chen Zhang, Jiuheng Lin, Zhiyuan Liao +1
Adapting large language models (LLMs) to low-resource languages (LRLs) is constrained by the scarcity of task data and computational resources. Although Proxy Tuning offers a logit…
How Much Do Large Language Models Know about Human Motion? A Case Study in 3D Avatar Control
Kunhang Li, Jason Naradowsky, Yansong Feng +1
We explore the human motion knowledge of Large Language Models (LLMs) through 3D avatar control. Given a motion instruction, we prompt LLMs to first generate a high-level movement…
Motion Generation from Fine-grained Textual Descriptions
Kunhang Li, Yansong Feng
The task of text2motion is to generate human motion sequences from given textual descriptions, where the model explores diverse mappings from natural language instructions to human…