18 citations · 40 across the 20 of their papers we have counts for
4 papers · 1 filter
Tevatron-Elastic: A Unified Abstraction for Training Elastic Retrievers and Rerankers
Yu Wang, Shengyao Zhuang, Xueguang Ma +4
A single model scale challenges the flexibility of a production retrieval system: some settings need it faster, others need a smaller index, and the right trade-off changes with th…
Beyond Correctness: Rewarding Faithful Reasoning in Retrieval-Augmented Generation
Zhichao Xu, Zongyu Wu, Yun Zhou +9
Inspired by the success of reinforcement learning (RL) in Large Language Model (LLM) training for domains like math and code, recent work has begun training LLMs to dynamically pla…
A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness
Fali Wang, Zhiwei Zhang, Xianren Zhang +11
Large language models (LLMs) have demonstrated emergent abilities in text generation, question answering, and reasoning, facilitating various tasks and domains. Despite their profi…
Catastrophic Failure of LLM Unlearning via Quantization
Zhiwei Zhang, Fali Wang, Xiaomin Li +6
Large language models (LLMs) have shown remarkable proficiency in generating text, benefiting from extensive training on vast textual corpora. However, LLMs may also acquire unwant…