5 citations · 8 across the 28 of their papers we have counts for
5 papers · 1 filter
Concise and Sufficient Sub-Sentence Citations for Retrieval-Augmented Generation
Guo Chen, Qiuyuan Li, Qiuxian Li +3
In retrieval-augmented generation (RAG) question answering systems, generating citations for large language model (LLM) outputs enhances verifiability and helps users identify pote…
M-BRe: Discovering Training Samples for Relation Extraction from Unlabeled Texts with Large Language Models
Zexuan Li, Hongliang Dai, Piji Li
For Relation Extraction (RE), the manual annotation of training data may be prohibitively expensive, since the sentences that contain the target relations in texts can be very scar…
Investigating Advanced Reasoning of Large Language Models via Black-Box Environment Interaction
Congchi Yin, Tianyi Wu, Yankai Shu +5
Existing tasks fall short in evaluating reasoning ability of Large Language Models (LLMs) in an interactive, unknown environment. This deficiency leads to the isolated assessment o…
Generating Diverse Training Samples for Relation Extraction with Large Language Models
Zexuan Li, Hongliang Dai, Piji Li
Using Large Language Models (LLMs) to generate training data can potentially be a preferable way to improve zero or few-shot NLP tasks. However, many problems remain to be investig…
ReFreeKV: Towards Threshold-Free KV Cache Compression
Xuanfan Ni, Liyan Xu, Chenyang Lyu +6
To reduce memory consumption during LLM inference, a handful of methods have been proposed for KV cache pruning. While these techniques can accomplish lossless memory reduction on…