Proactively Reducing the Hate Intensity of Online Posts via Hate Speech Normalization. - Sarah Masud; Manjot Bedi; Mohammad Aflah Khan; Md. Shad Akhtar; Tanmoy Chakraborty 002 (KDD, 2022)

Overview of the HASOC Subtrack at FIRE 2023: Identification of Tokens Contributing to Explicit Hate in English by Span Detection. - Sarah Masud; Mohammad Aflah Khan; Md. Shad Akhtar; Tanmoy Chakraborty 002 (FIRE (Working Notes), 2023)

Overview of the HASOC Subtracks at FIRE 2023: Detection of Hate Spans and Conversational Hate-Speech. - Shrey Satapara; Sarah Masud; Hiren Madhu; Mohammad Aflah Khan; Md. Shad Akhtar; Tanmoy Chakraborty 002; Sandip Modha; Thomas Mandl 001 (FIRE, 2023)

The Art of Embedding Fusion: Optimizing Hate Speech Detection. - Mohammad Aflah Khan; Neemesh Yadav; Mohit Jain; Sanyam Goyal (Tiny Papers @ ICLR, 2023)

Beyond Negativity: Re-Analysis and Follow-Up Experiments on Hope Speech Detection. - Neemesh Yadav; Mohammad Aflah Khan; Diksha Sethi; Raghav Sahni (Tiny Papers @ ICLR, 2023)

Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling. - Stella Biderman; Hailey Schoelkopf; Quentin Gregory Anthony; Herbie Bradley; Kyle O'Brien; Eric Hallahan; Mohammad Aflah Khan; Shivanshu Purohit; USVSN Sai Prashanth; Edward Raff; Aviya Skowron; Lintang Sutawika; et al. (ICML, 2023)

Probing Critical Learning Dynamics of PLMs for Hate Speech Detection. - Sarah Masud; Mohammad Aflah Khan; Vikram Goyal; Md. Shad Akhtar; Tanmoy Chakraborty 002 (EACL (Findings), 2024)

The Duality of Hope: A Critical Examination of Controversial Annotations in HopeEDI. - Mohammad Aflah Khan; Neemesh Yadav; Diksha Sethi; Raghav Sahni (Tiny Papers @ ICLR, 2024)

Towards Reliable Latent Knowledge Estimation in LLMs: In-Context Learning vs. Prompting Based Factual Knowledge Extraction. - Qinyuan Wu; Mohammad Aflah Khan; Soumi Das; Vedant Nanda; Bishwamittra Ghosh; Camila Kolling; Till Speicher; Laurent Bindschaedler; Krishna P. Gummadi; Evimaria Terzi (CoRR, 2024)

Understanding Memorisation in LLMs: Dynamics, Influencing Factors, and Implications. - Till Speicher; Mohammad Aflah Khan; Qinyuan Wu; Vedant Nanda; Soumi Das; Bishwamittra Ghosh; Krishna P. Gummadi; Evimaria Terzi (CoRR, 2024)

QUENCH: Measuring the gap between Indic and Non-Indic Contextual General Reasoning in LLMs. - Mohammad Aflah Khan; Neemesh Yadav; Sarah Masud; Md. Shad Akhtar (COLING, 2025)

Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon. - USVSN Sai Prashanth; Alvin Deng; Kyle O'Brien; Jyothir S. V; Mohammad Aflah Khan; Jaydeep Borkar; Christopher A. Choquette-Choo; Jacob Ray Fuehne; Stella Biderman; Tracy Ke; Katherine Lee; Naomi Saphra (ICLR, 2025)

Towards Reliable Latent Knowledge Estimation in LLMs: Zero-Prompt Many-Shot Based Factual Knowledge Extraction. - Qinyuan Wu; Mohammad Aflah Khan; Soumi Das; Vedant Nanda; Bishwamittra Ghosh; Camila Kolling; Till Speicher; Laurent Bindschaedler; Krishna P. Gummadi; Evimaria Terzi (WSDM, 2025)

Revisiting Privacy, Utility, and Efficiency Trade-offs when Fine-Tuning Large Language Models. - Soumi Das; Camila Kolling; Mohammad Aflah Khan; Mahsa Amani; Bishwamittra Ghosh; Qinyuan Wu; Till Speicher; Krishna P. Gummadi (CoRR, 2025)

Rethinking Memorization Measures and their Implications in Large Language Models. - Bishwamittra Ghosh; Soumi Das; Qinyuan Wu; Mohammad Aflah Khan; Krishna P. Gummadi; Evimaria Terzi; Deepak Garg (CoRR, 2025)

TokenSmith: Streamlining Data Editing, Search, and Inspection for Large-Scale Language Model Training and Interpretability. - Mohammad Aflah Khan; Ameya Godbole; Johnny Tian-Zheng Wei; Ryan Wang; James Flemings; Krishna P. Gummadi; Willie Neiswanger; Robin Jia (CoRR, 2025)

Rote Learning Considered Useful: Generalizing over Memorized Data in LLMs. - Qinyuan Wu; Soumi Das; Mahsa Amani; Bishwamittra Ghosh; Mohammad Aflah Khan; Krishna P. Gummadi; Muhammad Bilal Zafar (CoRR, 2025)