180 citations · 220 across the 26 of their papers we have counts for
9 papers · 1 filter
AtomR: Atomic Operator-Empowered Large Language Models for Heterogeneous Knowledge Reasoning
Amy Xin, Jinxin Liu, Zijun Yao +4
Despite the outstanding capabilities of large language models (LLMs), knowledge-intensive reasoning still remains a challenging task due to LLMs' limitations in compositional reaso…
LongReward: Improving Long-context Large Language Models with AI Feedback
Jiajie Zhang, Zhongni Hou, Xin Lv +7
Though significant advancements have been achieved in developing long-context large language models (LLMs), the compromised quality of LLM-synthesized data for supervised fine-tuni…
LongCite: Enabling LLMs to Generate Fine-grained Citations in Long-context QA
Jiajie Zhang, Yushi Bai, Xin Lv +8
Though current long-context large language models (LLMs) have demonstrated impressive capacities in answering user questions based on extensive text, the lack of citations in their…
ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools
Team GLM, :, Aohan Zeng +56
We introduce ChatGLM, an evolving family of large language models that we have been developing over time. This report primarily focuses on the GLM-4 language series, which includes…
Aligning Teacher with Student Preferences for Tailored Training Data Generation
Yantao Liu, Zhao Zhang, Zijun Yao +3
Large Language Models (LLMs) have shown significant promise as copilots in various tasks. Local deployment of LLMs on edge devices is necessary when handling privacy-sensitive data…
SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation
Zijun Yao, Weijian Qi, Liangming Pan +5
This paper introduces Self-aware Knowledge Retrieval (SeaKR), a novel adaptive RAG model that extracts self-aware uncertainty of LLMs from their internal states. SeaKR activates re…
Untangle the KNOT: Interweaving Conflicting Knowledge and Reasoning Skills in Large Language Models
Yantao Liu, Zijun Yao, Xin Lv +5
Providing knowledge documents for large language models (LLMs) has emerged as a promising solution to update the static knowledge inherent in their parameters. However, knowledge i…
KB-Plugin: A Plug-and-play Framework for Large Language Models to Induce Programs over Low-resourced Knowledge Bases
Jiajie Zhang, Shulin Cao, Linmei Hu +3
Program induction (PI) has become a promising paradigm for using knowledge bases (KBs) to help large language models (LLMs) answer complex knowledge-intensive questions. Nonetheles…
How Proficient Are Large Language Models in Formal Languages? An In-Depth Insight for Knowledge Base Question Answering
Jinxin Liu, Shulin Cao, Jiaxin Shi +5
Knowledge Base Question Answering (KBQA) aims to answer natural language questions based on facts in knowledge bases. A typical approach to KBQA is semantic parsing, which translat…