Mohammad Aflah Khan

Hi, I'm Aflah, a research software engineer at the Max Planck Institute for Software Systems. My primary focus is on advancing our understanding of large language models (LLMs), evaluating their capabilities, and developing AI powered co-pilots to support researchers. Previously, I’ve worked on projects aimed at reducing hate speech on social media and other applications under NLP for social good.

Publications

QUENCH: Measuring the gap between Indic and Non-Indic Contextual General Reasoning in LLMs

QUENCH: Measuring the gap between Indic and Non-Indic Contextual General Reasoning in LLMs

Mohammad Aflah Khan, Neemesh Yadav, Sarah Masud, Md. Shad Akhtar

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Understanding Memorisation in LLMs: Dynamics, Influencing Factors, and Implications

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

arXiv.org 2024

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Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon

Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon

USVSN Sai Prashanth, Alvin Deng, Kyle O'Brien, V JyothirS, Mohammad Aflah Khan, Jaydeep Borkar, Christopher A. Choquette-Choo, Jacob Ray Fuehne, Stella Biderman, Tracy Ke, Katherine Lee, Naomi Saphra

arXiv.org 2024

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Towards Reliable Latent Knowledge Estimation in LLMs: Zero-Prompt Many-Shot Based Factual Knowledge Extraction

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

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Probing Critical Learning Dynamics of PLMs for Hate Speech Detection

Probing Critical Learning Dynamics of PLMs for Hate Speech Detection

Sarah Masud, Mohammad Aflah Khan, Vikram Goyal, Md. Shad Akhtar, Tanmoy Chakraborty

Findings 2024

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Overview of the HASOC Subtracks at FIRE 2023: Detection of Hate Spans and Conversational Hate-Speech

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, Sandip J Modha, Thomas Mandl

Fire 2023

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Overview of the HASOC Subtrack at FIRE 2023: Identification of Tokens Contributing to Explicit Hate in English by Span Detection

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

Fire 2023

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The Art of Embedding Fusion: Optimizing Hate Speech Detection

The Art of Embedding Fusion: Optimizing Hate Speech Detection

Mohammad Aflah Khan, Neemesh Yadav, Mohit Jain, Sanyam Goyal

Tiny Papers @ ICLR 2023

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Beyond Negativity: Re-Analysis and Follow-Up Experiments on Hope Speech Detection

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

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Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling

Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling

Stella Biderman, Hailey Schoelkopf, Quentin G. Anthony, Herbie Bradley, Kyle O'Brien, Eric Hallahan, Mohammad Aflah Khan, Shivanshu Purohit, USVSN Sai Prashanth, Edward Raff, Aviya Skowron, Lintang Sutawika, Oskar van der Wal

International Conference on Machine Learning 2023

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Proactively Reducing the Hate Intensity of Online Posts via Hate Speech Normalization

Proactively Reducing the Hate Intensity of Online Posts via Hate Speech Normalization

Sarah Masud, Manjot Bedi, Mohammad Aflah Khan, Md. Shad Akhtar, Tanmoy Chakraborty

Knowledge Discovery and Data Mining 2022

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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

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, K. Gummadi, Evimaria Terzi

arXiv.org 2024

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