1 citations · 2 across the 3 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★ 1 cited
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…