7 citations · 18 across the 11 of their papers we have counts for
5 papers · 1 filter
SiRA: Sparse Mixture of Low Rank Adaptation
Yun Zhu, Nevan Wichers, Chu-Cheng Lin +8
Parameter Efficient Tuning has been an prominent approach to adapt the Large Language Model to downstream tasks. Most previous works considers adding the dense trainable parameters…
Fusion-Eval: Integrating Assistant Evaluators with LLMs
Lei Shu, Nevan Wichers, Liangchen Luo +4
Evaluating natural language systems poses significant challenges, particularly in the realms of natural language understanding and high-level reasoning. In this paper, we introduce…
Critique Ability of Large Language Models
Liangchen Luo, Zi Lin, Yinxiao Liu +4
Critical thinking is essential for rational decision-making and problem-solving. This skill hinges on the ability to provide precise and reasoned critiques and is a hallmark of hum…
Towards an On-device Agent for Text Rewriting
Yun Zhu, Yinxiao Liu, Felix Stahlberg +7
Large Language Models (LLMs) have demonstrated impressive capabilities for text rewriting. Nonetheless, the large sizes of these models make them impractical for on-device inferenc…
RewriteLM: An Instruction-Tuned Large Language Model for Text Rewriting
Lei Shu, Liangchen Luo, Jayakumar Hoskere +5
Large Language Models (LLMs) have demonstrated impressive capabilities in creative tasks such as storytelling and E-mail generation. However, as LLMs are primarily trained on final…