3 papers
cs.SE2026
AgentCheck: A Reproduce-Intervene-Mitigate Workbench for LLM Agents over MCP
Aritra Mazumder, Nusrat jahan Lia
Tool-using LLM agents are mostly evaluated assuming all tools work. When a tool times out, returns a week-stale value, or has its description poisoned in deployment, the developer…
cs.CL2026
Learning What Not to Forget: Long-Horizon Agent Memory from a Few Kilobytes of Learning
Nusrat Jahan Lia, Aritra Mazumder
Long-running language-model systems accumulate interaction history that outgrows the context window, so they must continually evict. When an eviction policy drops a load-bearing de…
cs.CL2026
AgentCollabBench: Diagnosing When Good Agents Make Bad Collaborators
Aritra Mazumder, Shubhashis Roy Dipta, Nusrat Jahan Lia +10
Multi-agent systems achieve state-of-the-art outcomes through peer collaboration. However, when an agent in the pipeline silently drops a constraint, the system's final output may…