184 citations · 863 across the 46 of their papers we have counts for
5 papers · 1 filter
Establishing Knowledge Preference in Language Models
Sizhe Zhou, Sha Li, Yu Meng +3
Language models are known to encode a great amount of factual knowledge through pretraining. However, such knowledge might be insufficient to cater to user requests, requiring the…
InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales
Zhepei Wei, Wei-Lin Chen, Yu Meng
Retrieval-augmented generation (RAG) has shown promising potential to enhance the accuracy and factuality of language models (LMs). However, imperfect retrievers or noisy corpora c…
SimPO: Simple Preference Optimization with a Reference-Free Reward
Yu Meng, Mengzhou Xia, Danqi Chen
Direct Preference Optimization (DPO) is a widely used offline preference optimization algorithm that reparameterizes reward functions in reinforcement learning from human feedback…
Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs
Bowen Jin, Chulin Xie, Jiawei Zhang +8
Large language models (LLMs), while exhibiting exceptional performance, suffer from hallucinations, especially on knowledge-intensive tasks. Existing works propose to augment LLMs…
Grasping the Essentials: Tailoring Large Language Models for Zero-Shot Relation Extraction
Sizhe Zhou, Yu Meng, Bowen Jin +1
Relation extraction (RE) aims to identify semantic relationships between entities within text. Despite considerable advancements, existing models predominantly require extensive an…