activity
20242026
collaborators

11 papers

cs.CL2026

PaperMentor: A Human-Centered Multi-Agent Writing Tutor for AI Research Papers on Overleaf

Jiarui Liu, Terry Jingchen Zhang, Ryan Faulkner +17

Expert writing feedback from experienced researchers is critical for early-career scholars to improve their manuscripts, yet high-quality feedback often remains scarce because revi…

cs.LG2026

CLT-Forge: A Scalable Library for Cross-Layer Transcoders and Attribution Graphs

Florent Draye, Vedant Palit, Abir Harrasse +8

Mechanistic interpretability seeks to understand how Large Language Models (LLMs) represent and process information. Recent approaches based on dictionary learning and transcoders…

cs.CY2026

Preserving Historical Truth: Detecting Historical Revisionism in Large Language Models

Francesco Ortu, Joeun Yook, Punya Syon Pandey +5

Large language models (LLMs) are increasingly used as sources of historical information, motivating the need for scalable audits on contested events and politically charged narrati…

cs.LG2026

BinaryPPO: Efficient Policy Optimization for Binary Classification

Punya Syon Pandey, Zhijing Jin

Supervised fine-tuning (SFT) is the standard approach for binary classification tasks such as toxicity detection, factuality verification, and causal inference. However, SFT often…

cs.CR2026

TamperBench: Systematically Stress-Testing LLM Safety Under Fine-Tuning and Tampering

Saad Hossain, Tom Tseng, Punya Syon Pandey +8

As increasingly capable open-weight large language models (LLMs) are deployed, improving their tamper resistance against unsafe modifications, whether accidental or intentional, be…

cs.CL2026

Objective Matters: Fine-Tuning Objectives Shape Safety, Robustness, and Persona Drift

Daniel Vennemeyer, Punya Syon Pandey, Phan Anh Duong +2

Fine-tuning LLMs on benign data can still degrade alignment and adversarial robustness, yet direct analysis of the role of fine-tuning objectives in shaping these safety outcomes r…