68 citations · 87 across the 14 of their papers we have counts for
15 papers
ASAP: Agent-System Co-Design for Wall-Clock-Centered Auto HPO Research for ML Experiments
Taicheng Guo, Haomin Zhuang, Kehan Guo +4
Hyperparameter Optimization (HPO) is essential for maximizing machine learning model performance, and its core challenge is sample efficiency: finding strong configurations within…
MTSQL-R1: Towards Long-Horizon Multi-Turn Text-to-SQL via Agentic Training
Taicheng Guo, Hai Wang, ChaoChun Liu +4
Multi-turn Text-to-SQL aims to translate a user's conversational utterances into executable SQL while preserving dialogue coherence and grounding to the target schema. However, mos…
Prioritization First, Principles Second: An Adaptive Interpretation of Helpful, Honest, and Harmless Principles
Yue Huang, Chujie Gao, Yujun Zhou +5
The Helpful, Honest, and Harmless (HHH) principle is a foundational framework for aligning AI systems with human values. However, existing interpretations of the HHH principle ofte…
SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs?
Haomin Zhuang, Yihua Zhang, Kehan Guo +4
Recent advancements in LLMs unlearning have shown remarkable success in removing unwanted data-model influences while preserving the model's utility for legitimate knowledge. Despi…
Knowledge Graph Enhanced Language Agents for Recommendation
Taicheng Guo, Chaochun Liu, Hai Wang +5
Language agents have recently been used to simulate human behavior and user-item interactions for recommendation systems. However, current language agent simulations do not underst…
LabSafety Bench: Benchmarking LLMs on Safety Issues in Scientific Labs
Yujun Zhou, Jingdong Yang, Yue Huang +12
Artificial Intelligence (AI) is revolutionizing scientific research, yet its growing integration into laboratory environments presents critical safety challenges. Large language mo…
ScholarChemQA: Unveiling the Power of Language Models in Chemical Research Question Answering
Xiuying Chen, Tairan Wang, Taicheng Guo +7
Question Answering (QA) effectively evaluates language models' reasoning and knowledge depth. While QA datasets are plentiful in areas like general domain and biomedicine, academic…
Advanced Framework for Animal Sound Classification With Features Optimization
Qiang Yang, Xiuying Chen, Changsheng Ma +2
The automatic classification of animal sounds presents an enduring challenge in bioacoustics, owing to the diverse statistical properties of sound signals, variations in recording…
Flexible and Adaptable Summarization via Expertise Separation
Xiuying Chen, Mingzhe Li, Shen Gao +5
A proficient summarization model should exhibit both flexibility -- the capacity to handle a range of in-domain summarization tasks, and adaptability -- the competence to acquire n…
UGMAE: A Unified Framework for Graph Masked Autoencoders
Yijun Tian, Chuxu Zhang, Ziyi Kou +3
Generative self-supervised learning on graphs, particularly graph masked autoencoders, has emerged as a popular learning paradigm and demonstrated its efficacy in handling non-Eucl…
SceMQA: A Scientific College Entrance Level Multimodal Question Answering Benchmark
Zhenwen Liang, Kehan Guo, Gang Liu +7
The paper introduces SceMQA, a novel benchmark for scientific multimodal question answering at the college entrance level. It addresses a critical educational phase often overlooke…
Rethinking Scientific Summarization Evaluation: Grounding Explainable Metrics on Facet-aware Benchmark
Xiuying Chen, Tairan Wang, Qingqing Zhu +5
The summarization capabilities of pretrained and large language models (LLMs) have been widely validated in general areas, but their use in scientific corpus, which involves comple…
Are we making much progress? Revisiting chemical reaction yield prediction from an imbalanced regression perspective
Yihong Ma, Xiaobao Huang, Bozhao Nan +4
The yield of a chemical reaction quantifies the percentage of the target product formed in relation to the reactants consumed during the chemical reaction. Accurate yield predictio…
Large Language Model based Multi-Agents: A Survey of Progress and Challenges
Taicheng Guo, Xiuying Chen, Yaqi Wang +5
Large Language Models (LLMs) have achieved remarkable success across a wide array of tasks. Due to the impressive planning and reasoning abilities of LLMs, they have been used as a…
ReactionTeam: Teaming Experts for Divergent Thinking Beyond Typical Reaction Patterns
Taicheng Guo, Changsheng Ma, Xiuying Chen +6
Reaction prediction, a critical task in synthetic chemistry, is to predict the outcome of a reaction based on given reactants. Generative models like Transformer have typically bee…