collaborators

5 papers

cs.AI2026

Rethinking Literature Search Evaluation: Deep Research Helps, and Human Citation Lists Are Not a Ground Truth

Gaurav Sahu, Laurent Charlin, Christopher Pal

We study large-scale literature search from two complementary angles: improving the retrieval pipeline, and stress-testing the human reference list as an evaluation target. First,…

cs.AI2026

AInstein: Can LLMs Solve Research Problems From Parametric Memory Alone?

Shambhavi Mishra, Gaurav Sahu, Marco Pedersoli +3

Can large language models solve AI research problems using only their parametric knowledge, without fine-tuning, retrieval, or other external aids? We introduce AInstein, a framewo…

cs.AI2025

ReviewerToo: Should AI Join The Program Committee? A Look At The Future of Peer Review

Gaurav Sahu, Hugo Larochelle, Laurent Charlin +1

Peer review is the cornerstone of scientific publishing, yet it suffers from inconsistencies, reviewer subjectivity, and scalability challenges. We introduce ReviewerToo, a modular…

cs.CL2025

LitLLMs, LLMs for Literature Review: Are we there yet?

Shubham Agarwal, Gaurav Sahu, Abhay Puri +5

Literature reviews are an essential component of scientific research, but they remain time-intensive and challenging to write, especially due to the recent influx of research paper…

cs.CL2025

LitLLM: A Toolkit for Scientific Literature Review

Shubham Agarwal, Gaurav Sahu, Abhay Puri +5

Conducting literature reviews for scientific papers is essential for understanding research, its limitations, and building on existing work. It is a tedious task which makes an aut…