collaborators

18 papers

cs.AI2026

Beyond Static Leaderboards: Predictive Validity for the Evaluation of LLM Agents

Dhaval C. Patel, Kaoutar El Maghraoui, Shuxin Lin +58

Agent benchmarks are growing fast, but no single benchmark touches more than four or five of the dimensions that deployment exposes. This paper aggregates the largest coordinated d…

cs.SE2026

DynAMO:Dynamic Asset Management Orchestration via Topological Multi-Agent Scheduling

Kanishk Kushwaha, Vikrant Vinod Bansode, Harsh Vardhan +1

While LLM-powered agents offer end-to-end automation for industrial asset lifecycles, real-world Industry 4.0 deployment is hindered by latency, concurrency instability, and safety…

cs.AI2026

Evoflux: Inference-Time Evolution of Executable Tool Workflows for Compact Agents

Kushal Raj Bhandari, Ling Yue, Ching-Yun Ko +4

Compact language models (LMs) reduce cost, latency, and deployment risk for tool agents. Yet MCP-style tool use requires more than isolated function calling: an agent must discover…

cs.AI2026

Synthetic Scenario Generation for Evaluation of Industry 4.0 Agents

Sagar Chethan Kumar, Rohith Kanathur, Dhaval Patel +1

Industrial agent benchmarks require realistic evaluation scenarios that integrate telemetry, failure modes, maintenance records, and domain standards. However, existing benchmarks…

cs.AI2026

Beyond Final Answers: Auditing Trajectory-Level Hallucinations in Multi-Agent Industrial Workflows

Harshada Badave, Santosh Borse, Andrea Gomez +6

Large Language Models (LLMs) are increasingly deployed as autonomous agents that reason, use tools, and act over multiple steps. Yet most hallucination benchmarks still evaluate on…

cs.CL2026

Internalizing Tool Knowledge in Small Language Models via QLoRA Fine-Tuning

Yuval Shemla, Ayal Yakobe, Tanmay Agarwal +2

Large language models are increasingly used as planning components in agentic systems, but current tool-use pipelines often require full tool schemas to be included in every prompt…