1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2026
Steering Large Reasoning Models towards Concise Reasoning via Flow Matching
Yawei Li, Benjamin Bergner, Yinghan Zhao +3
Large Reasoning Models (LRMs) excel at complex reasoning tasks, but their efficiency is often hampered by overly verbose outputs. Prior steering methods attempt to address this iss…
cs.CL2024
Nearest Neighbor Speculative Decoding for LLM Generation and Attribution
Minghan Li, Xilun Chen, Ari Holtzman +4
Large language models (LLMs) often hallucinate and lack the ability to provide attribution for their generations. Semi-parametric LMs, such as kNN-LM, approach these limitations by…
cs.LG2024★ 1 cited
Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
Xuezhe Ma, Xiaomeng Yang, Wenhan Xiong +7
The quadratic complexity and weak length extrapolation of Transformers limits their ability to scale to long sequences, and while sub-quadratic solutions like linear attention and…