10 citations · 11 across the 11 of their papers we have counts for
5 papers · 1 filter
Your Teacher Can't Help You Here: Combating Supervision Fidelity Decay in On-Policy Distillation
Yanjiang Liu, Jie Lou, Xinyan Guan +7
On-policy distillation transfers reasoning capabilities by training a student model on its own generated trajectories using token-level feedback from a teacher. However, we identif…
Coupled Variational Reinforcement Learning for Language Model General Reasoning
Xueru Wen, Jie Lou, Yanjiang Liu +6
While reinforcement learning has achieved impressive progress in language model reasoning, it is constrained by the requirement for verifiable rewards. Recent verifier-free RL meth…
Beyond Isolated Dots: Benchmarking Structured Table Construction as Deep Knowledge Extraction
Tianyun Zhong, Guozhao Mo, Yanjiang Liu +9
With the emergence of large language models (LLMs), there is an expectation that LLMs can effectively extract explicit information from complex real-world documents (e.g., papers,…
SAISA: Towards Multimodal Large Language Models with Both Training and Inference Efficiency
Qianhao Yuan, Yanjiang Liu, Yaojie Lu +4
Multimodal Large Language Models (MLLMs) mainly fall into two architectures, each involving a trade-off between training and inference efficiency: embedding space alignment (e.g.,…
Mitigating Large Language Model Hallucinations via Autonomous Knowledge Graph-based Retrofitting
Xinyan Guan, Yanjiang Liu, Hongyu Lin +4
Incorporating factual knowledge in knowledge graph is regarded as a promising approach for mitigating the hallucination of large language models (LLMs). Existing methods usually on…