34 citations · 65 across the 10 of their papers we have counts for
5 papers · 1 filter
Understanding Enrichment in Reinforcement Learning
Jinwoo Kim, Shraddha Barke
When rewards are sparse, reinforcement learning with verifiable rewards (RLVR) often uses hints or intermediate guidance to generate more successful rollouts. This enrichment biase…
Agents as Software: A Programming Languages Agenda for Agent Reliability
Shraddha Barke, Adithya Murali
AI agents increasingly resemble software systems: they call tools, remember facts, follow policies, delegate work, and take actions with real consequences. % Yet the ``program'' of…
Tokengeist: Multi-Turn Attribution Tracing in Agentic Conversations
Jessica Tang, Shraddha Barke, Sharad Agarwal
When a language model produces a response in a multi-turn conversation, which tokens from prior turns shaped that answer, and how did those dependencies propagate across prior turn…
Willful Disobedience: Automatically Detecting Failures in Agentic Traces
Reshabh K Sharma, Shraddha Barke, Benjamin Zorn
AI agents are increasingly embedded in real software systems, where they execute multi-step workflows through multi-turn dialogue, tool invocations, and intermediate decisions. The…
AgentRx: Diagnosing AI Agent Failures from Execution Trajectories
Shraddha Barke, Arnav Goyal, Alind Khare +3
AI agents often fail in ways that are difficult to localize because executions are probabilistic, long-horizon, multi-agent, and mediated by noisy tool outputs. We address this gap…