3 citations · 3 across the 4 of their papers we have counts for
5 papers
Checking Fact with Better Retrieval: Dynamic Contrastive Learning for Evidence Retrieval
Zhongtian Hua, Yi Luo, Meijia Yu +1
In the field of multimodal fact checking, the accuracy of retrieving evidence from different modalities has a significant impact on the downstream claim verification process. Exist…
Tandem: Riding Together with Large and Small Language Models for Efficient Reasoning
Zichuan Fu, Xian Wu, Guojing Li +7
Recent advancements in large language models (LLMs) have catalyzed the rise of reasoning-intensive inference paradigms, where models perform explicit step-by-step reasoning before…
Xinyu: An Efficient LLM-based System for Commentary Generation
Yiquan Wu, Bo Tang, Chenyang Xi +13
Commentary provides readers with a deep understanding of events by presenting diverse arguments and evidence. However, creating commentary is a time-consuming task, even for skille…
Reasoning on Efficient Knowledge Paths:Knowledge Graph Guides Large Language Model for Domain Question Answering
Yuqi Wang, Boran Jiang, Yi Luo +3
Large language models (LLMs), such as GPT3.5, GPT4 and LLAMA2 perform surprisingly well and outperform human experts on many tasks. However, in many domain-specific evaluations, th…
NewsBench: A Systematic Evaluation Framework for Assessing Editorial Capabilities of Large Language Models in Chinese Journalism
Miao Li, Ming-Bin Chen, Bo Tang +8
We present NewsBench, a novel evaluation framework to systematically assess the capabilities of Large Language Models (LLMs) for editorial capabilities in Chinese journalism. Our c…