1 citations · 1 across the 1 of their papers we have counts for
4 papers
Advancing AI Research Assistants with Expert-Involved Learning
Tianyu Liu, Simeng Han, Hanchen Wang +27
Large language models (LLMs) and large multimodal models (LMMs) promise to accelerate biomedical discovery, yet their reliability remains unclear. We introduce ARIEL (AI Research A…
InstructDiff: Domain-Adaptive Data Selection via Differential Entropy for Efficient LLM Fine-Tuning
Junyou Su, He Zhu, Xiao Luo +6
Supervised fine-tuning (SFT) is fundamental to adapting large language models, yet training on complete datasets incurs prohibitive costs with diminishing returns. Existing data se…
Scaling Equitable Reflection Assessment in Education via Large Language Models and Role-Based Feedback Agents
Chenyu Zhang, Xiaohang Luo
Formative feedback is widely recognized as one of the most effective drivers of student learning, yet it remains difficult to implement equitably at scale. In large or low-resource…
A Bi-consolidating Model for Joint Relational Triple Extraction
Xiaocheng Luo, Yanping Chen, Ruixue Tang +3
Current methods to extract relational triples directly make a prediction based on a possible entity pair in a raw sentence without depending on entity recognition. The task suffers…