38 citations · 40 across the 8 of their papers we have counts for
8 papers
Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data
Shiping Yang, Jie Wu, Wenbiao Ding +7
Robustness has become a critical attribute for the deployment of RAG systems in real-world applications. Existing research focuses on robustness to explicit noise (e.g., document s…
MuDAF: Long-Context Multi-Document Attention Focusing through Contrastive Learning on Attention Heads
Weihao Liu, Ning Wu, Shiping Yang +4
Large Language Models (LLMs) frequently show distracted attention due to irrelevant information in the input, which severely impairs their long-context capabilities. Inspired by re…
Fostering Natural Conversation in Large Language Models with NICO: a Natural Interactive COnversation dataset
Renliang Sun, Mengyuan Liu, Shiping Yang +3
Benefiting from diverse instruction datasets, contemporary Large Language Models (LLMs) perform effectively as AI assistants in collaborating with humans. However, LLMs still strug…
A New Benchmark and Reverse Validation Method for Passage-level Hallucination Detection
Shiping Yang, Renliang Sun, Xiaojun Wan
Large Language Models (LLMs) have shown their ability to collaborate effectively with humans in real-world scenarios. However, LLMs are apt to generate hallucinations, i.e., makeup…
Multi-level Contrastive Learning for Script-based Character Understanding
Dawei Li, Hengyuan Zhang, Yanran Li +1
In this work, we tackle the scenario of understanding characters in scripts, which aims to learn the characters' personalities and identities from their utterances. We begin by ana…
A New Dataset and Empirical Study for Sentence Simplification in Chinese
Shiping Yang, Renliang Sun, Xiaojun Wan
Sentence Simplification is a valuable technique that can benefit language learners and children a lot. However, current research focuses more on English sentence simplification. Th…
Human-like Summarization Evaluation with ChatGPT
Mingqi Gao, Jie Ruan, Renliang Sun +3
Evaluating text summarization is a challenging problem, and existing evaluation metrics are far from satisfactory. In this study, we explored ChatGPT's ability to perform human-lik…
Fine-grained Contrastive Learning for Definition Generation
Hengyuan Zhang, Dawei Li, Shiping Yang +1
Recently, pre-trained transformer-based models have achieved great success in the task of definition generation (DG). However, previous encoder-decoder models lack effective repres…