collaborators

7 papers

cs.CL2026

Register Shifts Break LLM Safety: A Bengali Benchmark with Culturally Grounded Harms

Naymul Islam, Nusrat Jahan Lia, Shubhashis Roy Dipta +2

Bengali is the seventh-most-spoken language globally, yet LLM safety evaluation remains overwhelmingly English-centric. We introduce BanglaSafe, a benchmark of 879 Bengali prompts…

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…

cs.CL2026

Cross-Lingual Sentiment Misalignment: Auditing Multilingual Language Models for Inversion Risk, Dialectal Representation, and Affective Stability

Nusrat Jahan Lia, Shubhashis Roy Dipta

Recent advances in multilingual representation learning aim to bridge the performance gap between high- and low-resource languages, yet their ability to preserve affective meaning…

cs.CL2025

Exploring Cross-Lingual Knowledge Transfer via Transliteration-Based MLM Fine-Tuning for Critically Low-resource Chakma Language

Adity Khisa, Nusrat Jahan Lia, Tasnim Mahfuz Nafis +4

As an Indo-Aryan language with limited available data, Chakma remains largely underrepresented in language models. In this work, we introduce a novel corpus of contextually coheren…