collaborators

5 papers

cs.AI2026

CoverSynth: Coverage-Guided Generation of Retrieval Evaluation Sets

Anahita Sharma, Apaar Shanker, Rishav Chakravarti +6

Enterprise agents need retrieval evaluation sets that expose domain-specific failures and guide developers towards efficient deployment tradeoffs. Neither expert-human-authored set…

cs.AI2026

Studying Without a Syllabus: Task-Agnostic Environment Preprocessing

Vinay Samuel, Varun Ursekar, Vijay S. Kalmath +3

Before an LLM agent tackles tasks in a new environment, it can inspect available corpora and tools and construct reusable resources such as indices, scripts, or procedural guidance…

cs.AI2026

CliniCARE-Bench: Clinical Calibrated Audit of Medical Reasoning in EHR

Veronica Chatrath, Bryan Zhu, George Pu +16

Large language models perform strongly on medical knowledge benchmarks, but reliable clinical deployment requires agents to conduct defensible investigations over heterogeneous, lo…

cs.AI2026

HarnessOpt-Bench: Evaluating LLMs at Harness Optimization

Varun Ursekar, Apaar Shanker, Yash Maurya +4

As LLMs are increasingly deployed within agentic systems, their capabilities depend not only on the model weights but also on the harness: the prompts, tools, control flow, memory,…

cs.AI2026

Insights Generator: Systematic Corpus-Level Trace Diagnostics for LLM Agents

Akshay Manglik, Apaar Shanker, Kaustubh Deshpande +6

Diagnosing failures in LLM agents remains largely manual. Practitioners inspect a small subset of execution traces, form ad-hoc hypotheses, and iterate. This process misses pattern…