collaborators

5 papers

cs.AI2026

Deep FinResearch Bench: Evaluating AI's Ability to Conduct Professional Financial Investment Research

Mirazul Haque, Antony Papadimitriou, Samuel Mensah +6

We introduce Deep FinResearch Bench, a practical and comprehensive evaluation framework for deep research (DR) agents in financial investment research. The benchmark assesses three…

cs.CL2026

Detecting Non-Membership in LLM Training Data via Rank Correlations

Pranav Shetty, Mirazul Haque, Zhiqiang Ma +1

As large language models (LLMs) are trained on increasingly vast and opaque text corpora, determining which data contributed to training has become essential for copyright enforcem…

cs.CL2025

Perturb Your Data: Paraphrase-Guided Training Data Watermarking

Pranav Shetty, Mirazul Haque, Petr Babkin +3

Training data detection is critical for enforcing copyright and data licensing, as Large Language Models (LLM) are trained on massive text corpora scraped from the internet. We pre…

cs.LG2025

Efficiency Robustness of Dynamic Deep Learning Systems

Ravishka Rathnasuriya, Tingxi Li, Zexin Xu +4

Deep Learning Systems (DLSs) are increasingly deployed in real-time applications, including those in resourceconstrained environments such as mobile and IoT devices. To address eff…

cs.LG2025

Towards Effectively Leveraging Execution Traces for Program Repair with Code LLMs

Mirazul Haque, Petr Babkin, Farima Farmahinifarahani +1

Large Language Models (LLMs) show promising performance on various programming tasks, including Automatic Program Repair (APR). However, most approaches to LLM-based APR are limite…