Arka Pal - RankMe

24 papers A* 4A 1Journal 17Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Dynamic Delayed Tree Expansion For Improved Multi-Path Speculative Decoding. CoRR Rahul Krishna Thomas, Teo Kitanovski, Micah Goldblum, Arka Pal
2026	J	`jnl`	Greedy Multi-Path Block Verification for Faster Decoding in Speculative Sampling. CoRR Rahul Krishna Thomas, Arka Pal
2026	J	`jnl`	Privacy-Preserving Mechanisms Enable Cheap Verifiable Inference of LLMs. CoRR Arka Pal, Louai Zahran, William Gvozdjak, Akilesh Potti, Micah Goldblum
2025	J	`jnl`	An Attack to Break Permutation-Based Private Third-Party Inference Schemes for LLMs. CoRR Rahul Krishna Thomas, Louai Zahran, Erica Choi, Akilesh Potti, Micah Goldblum, Arka Pal
2025	J	`jnl`	Cascade: Token-Sharded Private LLM Inference. CoRR Rahul Krishna Thomas, Louai Zahran, Erica Choi, Akilesh Potti, Micah Goldblum, Arka Pal
2025	J	`jnl`	Global Resolution: Optimal Multi-Draft Speculative Sampling via Convex Minimization. CoRR Rahul Krishna Thomas, Arka Pal
2025	A*	`conf`	Hidden No More: Attacking and Defending Private Third-Party LLM Inference. ICML Rahul Krishna Thomas, Louai Zahran, Erica Choi, Akilesh Potti, Micah Goldblum, Arka Pal
2025	J	`jnl`	Incoherent Beliefs & Inconsistent Actions in Large Language Models. CoRR Arka Pal, Teo Kitanovski, Arthur Liang, Akilesh Potti, Micah Goldblum
2025	A*	`conf`	LiveBench: A Challenging, Contamination-Limited LLM Benchmark. ICLR Colin White, Samuel Dooley, Manley Roberts, Arka Pal, Benjamin Feuer, Siddhartha Jain, Ravid Shwartz-Ziv, Neel Jain, Khalid Saifullah, Sreemanti Dey, Shubh-Agrawal, Sandeep Singh Sandha, Siddartha V. Naidu, Chinmay Hegde, Yann LeCun, Tom Goldstein, Willie Neiswanger, Micah Goldblum
2024	A	`conf`	A Soft Robotic System Automatically Learns Precise Agile Motions Without Model Information. IROS Simon Bachhuber, Alexander Pawluchin, Arka Pal, Ivo Boblan, Thomas Seel
2024	J	`jnl`	A Soft Robotic System Automatically Learns Precise Agile Motions Without Model Information. CoRR Simon Bachhuber, Alexander Pawluchin, Arka Pal, Ivo Boblan, Thomas Seel
2024	A*	`conf`	Large Language Models Must Be Taught to Know What They Don't Know. NeurIPS Sanyam Kapoor, Nate Gruver, Manley Roberts, Katie Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Gordon Wilson
2024	J	`jnl`	Large Language Models Must Be Taught to Know What They Don't Know. CoRR Sanyam Kapoor, Nate Gruver, Manley Roberts, Katherine M. Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Gordon Wilson
2024	J	`jnl`	LiveBench: A Challenging, Contamination-Free LLM Benchmark. CoRR Colin White, Samuel Dooley, Manley Roberts, Arka Pal, Benjamin Feuer, Siddhartha Jain, Ravid Shwartz-Ziv, Neel Jain, Khalid Saifullah, Siddartha Naidu, Chinmay Hegde, Yann LeCun, Tom Goldstein, Willie Neiswanger, Micah Goldblum
2024	J	`jnl`	Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive. CoRR Arka Pal, Deep Karkhanis, Samuel Dooley, Manley Roberts, Siddartha Naidu, Colin White
2024	J	`jnl`	vTune: Verifiable Fine-Tuning for LLMs Through Backdooring. CoRR Eva Zhang, Arka Pal, Akilesh Potti, Micah Goldblum
2023	J	`jnl`	Giraffe: Adventures in Expanding Context Lengths in LLMs. CoRR Arka Pal, Deep Karkhanis, Manley Roberts, Samuel Dooley, Arvind Sundararajan, Siddartha Naidu
2018	—	`conf`	SCAN: Learning Hierarchical Compositional Visual Concepts. ICLR (Poster) Irina Higgins, Nicolas Sonnerat, Loic Matthey, Arka Pal, Christopher P. Burgess, Matko Bosnjak, Murray Shanahan, Matthew M. Botvinick, Demis Hassabis, Alexander Lerchner
2018	J	`jnl`	Understanding disentangling in β-VAE. CoRR Christopher P. Burgess, Irina Higgins, Arka Pal, Loïc Matthey, Nick Watters, Guillaume Desjardins, Alexander Lerchner
2017	A*	`conf`	DARLA: Improving Zero-Shot Transfer in Reinforcement Learning. ICML Irina Higgins, Arka Pal, Andrei A. Rusu, Loïc Matthey, Christopher P. Burgess, Alexander Pritzel, Matthew M. Botvinick, Charles Blundell, Alexander Lerchner
2017	J	`jnl`	DARLA: Improving Zero-Shot Transfer in Reinforcement Learning. CoRR Irina Higgins, Arka Pal, Andrei A. Rusu, Loïc Matthey, Christopher P. Burgess, Alexander Pritzel, Matthew M. Botvinick, Charles Blundell, Alexander Lerchner
2017	J	`jnl`	SCAN: Learning Abstract Hierarchical Compositional Visual Concepts. CoRR Irina Higgins, Nicolas Sonnerat, Loïc Matthey, Arka Pal, Christopher P. Burgess, Matthew M. Botvinick, Demis Hassabis, Alexander Lerchner
2017	—	`conf`	beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework. ICLR (Poster) Irina Higgins, Loïc Matthey, Arka Pal, Christopher P. Burgess, Xavier Glorot, Matthew M. Botvinick, Shakir Mohamed, Alexander Lerchner
2016	J	`jnl`	Early Visual Concept Learning with Unsupervised Deep Learning. CoRR Irina Higgins, Loïc Matthey, Xavier Glorot, Arka Pal, Benigno Uria, Charles Blundell, Shakir Mohamed, Alexander Lerchner