24 citations · 30 across the 17 of their papers we have counts for
12 papers · 1 filter
RM-Bench: Benchmarking Reward Models of Language Models with Subtlety and Style
Yantao Liu, Zijun Yao, Rui Min +3
Reward models are critical in techniques like Reinforcement Learning from Human Feedback (RLHF) and Inference Scaling Laws, where they guide language model alignment and select opt…
Towards Understanding Safety Alignment: A Mechanistic Perspective from Safety Neurons
Jianhui Chen, Xiaozhi Wang, Zijun Yao +3
Large language models (LLMs) excel in various capabilities but pose safety risks such as generating harmful content and misinformation, even after safety alignment. In this paper,…
TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios
Xiaokang Zhang, Sijia Luo, Bohan Zhang +12
We introduce TableLLM, a robust large language model (LLM) with 8 billion parameters, purpose-built for proficiently handling tabular data manipulation tasks, whether they are embe…
Probabilistic Tree-of-thought Reasoning for Answering Knowledge-intensive Complex Questions
Shulin Cao, Jiajie Zhang, Jiaxin Shi +5
Large language models (LLMs) are capable of answering knowledge-intensive complex questions with chain-of-thought (CoT) reasoning. However, they tend to generate factually incorrec…
LittleMu: Deploying an Online Virtual Teaching Assistant via Heterogeneous Sources Integration and Chain of Teach Prompts
Shangqing Tu, Zheyuan Zhang, Jifan Yu +5
Teaching assistants have played essential roles in the long history of education. However, few MOOC platforms are providing human or virtual teaching assistants to support learning…
VisKoP: Visual Knowledge oriented Programming for Interactive Knowledge Base Question Answering
Zijun Yao, Yuanyong Chen, Xin Lv +8
We present Visual Knowledge oriented Programming platform (VisKoP), a knowledge base question answering (KBQA) system that integrates human into the loop to edit and debug the know…
KoRC: Knowledge oriented Reading Comprehension Benchmark for Deep Text Understanding
Zijun Yao, Yantao Liu, Xin Lv +4
Deep text understanding, which requires the connections between a given document and prior knowledge beyond its text, has been highlighted by many benchmarks in recent years. Howev…
KoLA: Carefully Benchmarking World Knowledge of Large Language Models
Jifan Yu, Xiaozhi Wang, Shangqing Tu +32
The unprecedented performance of large language models (LLMs) necessitates improvements in evaluations. Rather than merely exploring the breadth of LLM abilities, we believe meticu…
GLM-Dialog: Noise-tolerant Pre-training for Knowledge-grounded Dialogue Generation
Jing Zhang, Xiaokang Zhang, Daniel Zhang-Li +10
We present GLM-Dialog, a large-scale language model (LLM) with 10B parameters capable of knowledge-grounded conversation in Chinese using a search engine to access the Internet kno…
Step out of KG: Knowledge Graph Completion via Knowledgeable Retrieval and Reading Comprehension
Xin Lv, Yankai Lin, Zijun Yao +4
Knowledge graphs, as the cornerstone of many AI applications, usually face serious incompleteness problems. In recent years, there have been many efforts to study automatic knowled…
Schema-Free Dependency Parsing via Sequence Generation
Boda Lin, Zijun Yao, Jiaxin Shi +6
Dependency parsing aims to extract syntactic dependency structure or semantic dependency structure for sentences. Existing methods suffer the drawbacks of lacking universality or h…
Interpretable and Low-Resource Entity Matching via Decoupling Feature Learning from Decision Making
Zijun Yao, Chengjiang Li, Tiansi Dong +6
Entity Matching (EM) aims at recognizing entity records that denote the same real-world object. Neural EM models learn vector representation of entity descriptions and match entiti…