14 citations · 72 across the 18 of their papers we have counts for
5 papers · 1 filter
MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction-Following
Renze Lou, Kai Zhang, Jian Xie +5
In the realm of large language models (LLMs), enhancing instruction-following capability often involves curating expansive training data. This is achieved through two primary schem…
Toward Zero-Shot Instruction Following
Renze Lou, Wenpeng Yin
This work proposes a challenging yet more realistic setting for zero-shot cross-task generalization: zero-shot instruction following, presuming the existence of a paragraph-style t…
Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflicts
Jian Xie, Kai Zhang, Jiangjie Chen +2
By providing external information to large language models (LLMs), tool augmentation (including retrieval augmentation) has emerged as a promising solution for addressing the limit…
PAGE: A Position-Aware Graph-Based Model for Emotion Cause Entailment in Conversation
Xiaojie Gu, Renze Lou, Lin Sun +1
Conversational Causal Emotion Entailment (C2E2) is a task that aims at recognizing the causes corresponding to a target emotion in a conversation. The order of utterances in the co…
Large Language Model Instruction Following: A Survey of Progresses and Challenges
Renze Lou, Kai Zhang, Wenpeng Yin
Task semantics can be expressed by a set of input-output examples or a piece of textual instruction. Conventional machine learning approaches for natural language processing (NLP)…