4 citations · 4 across the 4 of their papers we have counts for
6 papers
When Do Biological Reasoning Models Use Their Biological Inputs?
Ada Fang, Nikitha Thoduguli, Lukas Fesser +3
Biological reasoning models use post-training to connect LLMs to biological foundation model representations and biological text. Their benchmark accuracy is taken as evidence that…
Benchmarking AI Agents for Addressing Scientific Challenges Across Scales
Tianyu Liu, Allen Xin Wang, Antonia Panescu +30
AI agents are increasingly being developed to accelerate scientific discovery, yet their practical capabilities in real research settings remain poorly understood. Existing benchma…
Evaluating Relational Reasoning in LLMs with REL
Lukas Fesser, Yasha Ektefaie, Ada Fang +2
Relational reasoning is the ability to infer relations that jointly bind multiple entities, attributes, or variables. This ability is central to scientific reasoning, but existing…
AutoScientists: Self-Organizing Agent Teams for Long-Running Scientific Experimentation
Shanghua Gao, Ada Fang, Marinka Zitnik
Scientific research proceeds through iterative cycles of hypothesis generation, experiment design, execution, and revision. AI agents can automate parts of this process, but existi…
Tokenizing Loops of Antibodies
Ada Fang, Robert G. Alberstein, Simon Kelow +1
The complementarity-determining regions of antibodies are loop structures that are key to their interactions with antigens, and of high importance to the design of novel biologics.…
Empowering Biomedical Discovery with AI Agents
Shanghua Gao, Ada Fang, Yepeng Huang +6
We envision "AI scientists" as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate AI models and biomed…