Pedram Razavi — accepted AI-conference papers

2026

$\tau$-Knowledge: Evaluating Conversational Agents over Unstructured Knowledge

Quan Shi, Alexandra Zytek, Pedram Razavi, Karthik Narasimhan, Victor Barres

ICML 2026poster

Conversational agents are increasingly deployed in knowledge-intensive settings, where correct behavior depends on acquiring and applying domain-specific knowledge from large, proprietary, and unstructured corpora during live interactions with users. Yet most existing benchmarks evaluate retrieval o…

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2025

{$\tau$}-bench: A Benchmark for \underline{T}ool-\underline{A}gent-\underline{U}ser Interaction in Real-World Domains

Shunyu Yao, Noah Shinn, Pedram Razavi, Karthik R Narasimhan

ICLR 2025poster

Existing benchmarks for language agents do not set them up to interact with human users or follow domain-specific rules, both of which are vital to safe and realistic deployment. We propose $\tau$-bench, a benchmark with two domains (retail and airline) emulating dynamic conversations between a user…

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