24 citations · 30 across the 17 of their papers we have counts for
18 papers
RIDAR: Safeguarding Research Integrity in Autonomous Research Agents via Automated Detection and Runtime Intervention
Jiening Siow, Amy Xin, Junjie Wang +7
Autonomous research agents are increasingly used to automate large portions of scientific research, yet they are prone to research integrity violations (RIVs): behaviors that compr…
EurekAgent: Agent Environment Engineering is All You Need For Autonomous Scientific Discovery
Amy Xin, Jiening Siow, Junjie Wang +5
LLM-based agents have shown increasing potential in automating scientific discovery. Given an optimizable metric and an execution environment, they can propose, validate, and itera…
Guiding LLM Post-training Data Engineering with Model Internals from Sparse Autoencoders
Yi Jing, Zao Dai, Jinwu Hu +4
Model internals encode rich information about how a large language model (LLM) processes its training data; however, post-training data engineering largely relies on external signa…
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…
MoocRadar: A Fine-grained and Multi-aspect Knowledge Repository for Improving Cognitive Student Modeling in MOOCs
Jifan Yu, Mengying Lu, Qingyang Zhong +9
Student modeling, the task of inferring a student's learning characteristics through their interactions with coursework, is a fundamental issue in intelligent education. Although t…
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…
A Roadmap for Big Model
Sha Yuan, Hanyu Zhao, Shuai Zhao +97
With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm. Researchers have achieved various outcomes in the c…
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…
Program Transfer for Answering Complex Questions over Knowledge Bases
Shulin Cao, Jiaxin Shi, Zijun Yao +6
Program induction for answering complex questions over knowledge bases (KBs) aims to decompose a question into a multi-step program, whose execution against the KB produces the fin…
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…