Ahmed, Farhan

8 publications

ICLR 2026 GneissWeb: Preparing High Quality Data for LLMs at Scale Hajar Emami Gohari, Swanand Ravindra Kadhe, Yousaf Shah, Constantin M Adam, Abdulhamid Adebayo, Praneet Adusumilli, Farhan Ahmed, Nathalie Baracaldo, Santosh Subhashrao Borse, Yuan-Chi Chang, Xuan-Hong Dang, Nirmit Desai, Revital Eres, Ran Iwamoto, Alexei A. Karve, Yan Koyfman, Wei-Han Lee, Changchang Liu, Boris Lublinsky, Takuya Ohko, Pablo Pesce, Maroun Touma, Shiqiang Wang, Shalisha Witherspooon, Herbert Woisetschläger, David Wood, Kun-Lung Wu, Issei Yoshida, Syed Zawad, Petros Zerfos, Yi Zhou, Bishwaranjan Bhattacharjee

ICLR 2026 When Data Is the Algorithm: A Systematic Study and Curation of Preference Optimization Datasets Aladin Djuhera, Farhan Ahmed, Swanand Ravindra Kadhe, Syed Zawad, Heiko Ludwig, Holger Boche

NeurIPS 2025 Fixing It in Post: A Comparative Study of LLM Post-Training Data Quality and Model Performance Aladin Djuhera, Swanand Ravindra Kadhe, Syed Zawad, Farhan Ahmed, Heiko Ludwig, Holger Boche

ICLRW 2025 SafeMERGE: Preserving Safety Alignment in Fine-Tuned Large Language Models via Selective Layer-Wise Model Merging Aladin Djuhera, Swanand Kadhe, Farhan Ahmed, Syed Zawad, Holger Boche

ICLRW 2025 SafeMERGE: Preserving Safety Alignment in Fine-Tuned Large Language Models via Selective Layer-Wise Model Merging Aladin Djuhera, Swanand Ravindra Kadhe, Farhan Ahmed, Syed Zawad, Holger Boche

ICMLW 2024 Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs Swanand Kadhe, Farhan Ahmed, Dennis Wei, Nathalie Baracaldo, Inkit Padhi

NeurIPSW 2022 Benchmarking the Effect of Poisoning Defenses on the Security and Bias of the Final Model Nathalie Baracaldo, Kevin Eykholt, Farhan Ahmed, Yi Zhou, Shriti Priya, Taesung Lee, Swanand Kadhe, Yusong Tan, Sridevi Polavaram, Sterling Suggs, Yuyang Gao, David Slater

NeurIPSW 2022 On the Feasibility of Compressing Certifiably Robust Neural Networks Pratik Vaishnavi, Veena Krish, Farhan Ahmed, Kevin Eykholt, Amir Rahmati