159 citations · 798 across the 116 of their papers we have counts for
14 papers · 1 filter
Conformal Constrained Policy Optimization for Cost-Effective LLM Agents
Wenwen Si, Sooyong Jang, Insup Lee +1
While large language models (LLMs) have recently made tremendous progress towards solving challenging AI problems, they have done so at increasingly steep computational and API cos…
BrowserArena: Evaluating LLM Agents on Real-World Web Navigation Tasks
Sagnik Anupam, Davis Brown, Shuo Li +3
LLM web agents now browse and take actions on the open web, yet current agent evaluations are constrained to sandboxed environments or artificial tasks. We introduce BrowserArena,…
RAPID: An Efficient Reinforcement Learning Algorithm for Small Language Models
Lianghuan Huang, Sagnik Anupam, Insup Lee +2
Reinforcement learning (RL) has emerged as a promising strategy for finetuning small language models (SLMs) to solve targeted tasks such as math and coding. However, RL algorithms…
Beating the Winner's Curse via Inference-Aware Policy Optimization
Hamsa Bastani, Osbert Bastani, Bryce McLaughlin
There has been a surge of recent interest in automatically learning policies to target treatment decisions based on rich individual covariates. In addition, practitioners want conf…
Knowledgeable Language Models as Black-Box Optimizers for Personalized Medicine
Michael S. Yao, Osbert Bastani, Alma Andersson +3
The goal of personalized medicine is to discover a treatment regimen that optimizes a patient's clinical outcome based on their personal genetic and environmental factors. However,…
Active Learning for Neurosymbolic Program Synthesis
Celeste Barnaby, Qiaochu Chen, Ramya Ramalingam +2
The goal of active learning for program synthesis is to synthesize the desired program by asking targeted questions that minimize user interaction. While prior work has explored ac…