activity
20242026
most citedTxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools

8 citations · 17 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

When Sensors Fail: Temporal Sequence Models for Robust PPO under Sensor Drift

Kevin Vogt-Lowell, Theodoros Tsiligkaridis, Rodney Lafuente-Mercado +4

Real-world reinforcement learning systems must operate under distributional drift in their observation streams, yet most policy architectures implicitly assume fully observed and n…

cs.LG2026

Adaptive Time Series Reasoning via Segment Selection

Shvat Messica, Jiawen Zhang, Kevin Li +2

Time series reasoning tasks often start with a natural language question and require targeted analysis of a time series. Evidence may span the full series or appear in a few short…

cs.AI2025★ 6 cited

ToolUniverse: An open platform for democratizing AI scientists

Shanghua Gao, Richard Zhu, Pengwei Sui +8

AI scientists are emerging computational systems that serve as collaborative partners in discovery. These systems remain difficult to build because they are bespoke, tied to rigid…

cs.AI2025★ 8 cited

TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools

Shanghua Gao, Richard Zhu, Zhenglun Kong +5

Precision therapeutics require multimodal adaptive models that generate personalized treatment recommendations. We introduce TxAgent, an AI agent that leverages multi-step reasonin…

cs.LG2024★ 3 cited

UniTS: A Unified Multi-Task Time Series Model

Shanghua Gao, Teddy Koker, Owen Queen +3

Although pre-trained transformers and reprogrammed text-based LLMs have shown strong performance on time series tasks, the best-performing architectures vary widely across tasks, w…