6 papers
FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics
Qiran Zou, Hou Hei Lam, Wenhao Zhao +11
AI research agents accelerate ML research by automating hypothesis generation, experimentation, and empirical refinement. Existing agent strategies range from greedy hill-climbing…
Complementing reinforcement learning with SFT through logit averaging in the post training of LLMs
Xingwei Gan, Ying Zhu
We introduce a novel method that averages the logits of a frozen reference policy (e.g., SFT) and a trainable policy, and incorporate the method into Group Relative Policy Optimiza…
Navigating heterogeneous protein landscapes through geometry-aware smoothing
Srinivas Anumasa, Barath Chandran, Tingting Chen +15
The evolutionary fitness landscape of biological molecules is extremely sparse and heterogeneous, with functional sequences forming isolated dense ``islands'' within a vast combina…
AI-generated data contamination erodes pathological variability and diagnostic reliability
Hongyu He, Shaowen Xiang, Ye Zhang +15
Generative artificial intelligence (AI) is rapidly populating medical records with synthetic content, creating a feedback loop where future models are increasingly at risk of train…
Human-like Content Analysis for Generative AI with Language-Grounded Sparse Encoders
Yiming Tang, Arash Lagzian, Srinivas Anumasa +9
The rapid development of generative AI has transformed content creation, communication, and human development. However, this technology raises profound concerns in high-stakes doma…
DrVD-Bench: Do Vision-Language Models Reason Like Human Doctors in Medical Image Diagnosis?
Tianhong Zhou, Yin Xu, Yingtao Zhu +4
Vision-language models (VLMs) exhibit strong zero-shot generalization on natural images and show early promise in interpretable medical image analysis. However, existing benchmarks…