collaborators

6 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.CL2026

ExStrucTiny: A Benchmark for Schema-Variable Structured Information Extraction from Document Images

Mathieu Sibue, Andres Muñoz Garza, Samuel Mensah +4

Enterprise documents, such as forms and reports, embed critical information for downstream applications like data archiving, automated workflows, and analytics. Although generalist…

cs.CL2026

Entropy-Gated Branching for Efficient Test-Time Reasoning

Xianzhi Li, Ethan Callanan, Abdellah Ghassel +1

Test-time compute methods can significantly improve the reasoning capabilities and problem-solving accuracy of large language models (LLMs). However, these approaches require subst…

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.CL2025

CoCoLex: Confidence-guided Copy-based Decoding for Grounded Legal Text Generation

Santosh T. Y. S. S, Youssef Tarek Elkhayat, Oana Ichim +5

Due to their ability to process long and complex contexts, LLMs can offer key benefits to the Legal domain, but their adoption has been hindered by their tendency to generate unfai…