Arham Khan

15 papers Misc 1Journal 8Unranked 6
YearRankTypeTitle / Venue / Authors
2025 J jnl
AdaParse: An Adaptive Parallel PDF Parsing and Resource Scaling Engine.
CoRR
Carlo Siebenschuh, Kyle Hippe, Ozan Gökdemir, Alexander Brace, Arham Khan, Khalid Hossain, Yadu N. Babuji, Nicholas Chia, Venkatram Vishwanath, Rick Stevens, Arvind Ramanathan, Ian T. Foster, Robert Underwood
2025 J jnl
Revisiting ONE Simulator in IoV Research: Seeing the Forest Through the Trees.
IEEE Access
Hasan Mahmood Aminul Islam, Khalid Mahbub Khan, Mahamudur Rahman Maharaz, Angon Bhadra Antu, Farhad Billah, Shishir Majumder, Arham Khan
2025 — conf
SMURF: Federated Multimodal Retrieval for Scientific Data via Embedding Alignment.
eScience
Song Young Oh, Arham Khan, Ian T. Foster, Kyle Chard
2024 — conf
An End-to-End Programming Model for AI Engine Architectures.
HEART
Maksim Levental, Arham Khan, Ryan Chard, Kyle Chard, Stephen Neuendorffer, Ian T. Foster
2024 — conf
BraggHLS: High-Level Synthesis for Low-Latency Deep Neural Networks for Experimental Science.
HEART
Maksim Levental, Arham Khan, Ryan Chard, Kazutomo Yoshii, Kyle Chard, Ian T. Foster
2024 J jnl
LSHBloom: Memory-efficient, Extreme-scale Document Deduplication.
CoRR
Arham Khan, Robert Underwood, Carlo Siebenschuh, Yadu N. Babuji, Aswathy Ajith, Kyle Hippe, Ozan Gökdemir, Alexander Brace, Kyle Chard, Ian T. Foster
2024 J jnl
Mitigating Memorization In Language Models.
CoRR
Mansi Sakarvadia, Aswathy Ajith, Arham Khan, Nathaniel Hudson, Caleb Geniesse, Kyle Chard, Yaoqing Yang, Ian T. Foster, Michael W. Mahoney
2024 J jnl
SoK: On Finding Common Ground in Loss Landscapes Using Deep Model Merging Techniques.
CoRR
Arham Khan, Todd Nief, Nathaniel Hudson, Mansi Sakarvadia, Daniel Grzenda, Aswathy Ajith, Jordan Pettyjohn, Kyle Chard, Ian T. Foster
2023 — conf
An Efficient and Accurate Compression Ratio Estimation Model for SZx.
CLUSTER Workshops
Arham Khan, Sheng Di, Kai Zhao, Jinyang Liu, Kyle Chard, Ian T. Foster, Franck Cappello
2023 J jnl
Attention Lens: A Tool for Mechanistically Interpreting the Attention Head Information Retrieval Mechanism.
CoRR
Mansi Sakarvadia, Arham Khan, Aswathy Ajith, Daniel Grzenda, Nathaniel Hudson, André Bauer, Kyle Chard, Ian T. Foster
2023 — conf
LibPressio-Predict: Flexible and Fast Infrastructure For Inferring Compression Performance.
SC Workshops
Robert Underwood, Sheng Di, Sian Jin, Md Hasanur Rahman, Arham Khan, Franck Cappello
2023 — conf
Memory Injections: Correcting Multi-Hop Reasoning Failures During Inference in Transformer-Based Language Models.
BlackboxNLP@EMNLP
Mansi Sakarvadia, Aswathy Ajith, Arham Khan, Daniel Grzenda, Nathaniel Hudson, André Bauer, Kyle Chard, Ian T. Foster
2023 J jnl
Memory Injections: Correcting Multi-Hop Reasoning Failures during Inference in Transformer-Based Language Models.
CoRR
Mansi Sakarvadia, Aswathy Ajith, Arham Khan, Daniel Grzenda, Nathaniel Hudson, André Bauer, Kyle Chard, Ian T. Foster
2023 J jnl
OpenHLS: High-Level Synthesis for Low-Latency Deep Neural Networks for Experimental Science.
CoRR
Maksim Levental, Arham Khan, Ryan Chard, Kazutomo Yoshii, Kyle Chard, Ian T. Foster
2023 Misc conf
SECRE: Surrogate-Based Error-Controlled Lossy Compression Ratio Estimation Framework.
HiPC
Arham Khan, Sheng Di, Kai Zhao, Jinyang Liu, Kyle Chard, Ian T. Foster, Franck Cappello