Arka Pal

According to our database, Arka Pal authored at least 21 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Privacy-Preserving Mechanisms Enable Cheap Verifiable Inference of LLMs.

Arka Pal, Louai Zahran, William Gvozdjak, Akilesh Potti, Micah Goldblum

CoRR, February, 2026

Dynamic Delayed Tree Expansion For Improved Multi-Path Speculative Decoding.

Rahul Krishna Thomas, Teo Kitanovski, Micah Goldblum, Arka Pal

CoRR, February, 2026

Greedy Multi-Path Block Verification for Faster Decoding in Speculative Sampling.

Rahul Krishna Thomas, Arka Pal

CoRR, February, 2026

2025

Global Resolution: Optimal Multi-Draft Speculative Sampling via Convex Minimization.

Rahul Krishna Thomas, Arka Pal

CoRR, November, 2025

Incoherent Beliefs & Inconsistent Actions in Large Language Models.

Arka Pal, Teo Kitanovski, Arthur Liang, Akilesh Potti, Micah Goldblum

CoRR, November, 2025

Cascade: Token-Sharded Private LLM Inference.

Rahul Krishna Thomas, Louai Zahran, Erica Choi, Akilesh Potti, Micah Goldblum, Arka Pal

CoRR, July, 2025

An Attack to Break Permutation-Based Private Third-Party Inference Schemes for LLMs.

Rahul Krishna Thomas, Louai Zahran, Erica Choi, Akilesh Potti, Micah Goldblum, Arka Pal

CoRR, May, 2025

Hidden No More: Attacking and Defending Private Third-Party LLM Inference.

Rahul Krishna Thomas, Louai Zahran, Erica Choi, Akilesh Potti, Micah Goldblum, Arka Pal

Proceedings of the Forty-second International Conference on Machine Learning, 2025

LiveBench: A Challenging, Contamination-Limited LLM Benchmark.

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

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

vTune: Verifiable Fine-Tuning for LLMs Through Backdooring.

Eva Zhang, Arka Pal, Akilesh Potti, Micah Goldblum

CoRR, 2024

LiveBench: A Challenging, Contamination-Free LLM Benchmark.

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

CoRR, 2024

Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive.

Arka Pal, Deep Karkhanis, Samuel Dooley, Manley Roberts, Siddartha Naidu, Colin White

CoRR, 2024

Large Language Models Must Be Taught to Know What They Don't Know.

Sanyam Kapoor, Nate Gruver, Manley Roberts, Katie Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Gordon Wilson

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

A Soft Robotic System Automatically Learns Precise Agile Motions Without Model Information.

Simon Bachhuber, Alexander Pawluchin, Arka Pal, Ivo Boblan, Thomas Seel

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

2023

Giraffe: Adventures in Expanding Context Lengths in LLMs.

Arka Pal, Deep Karkhanis, Manley Roberts, Samuel Dooley, Arvind Sundararajan, Siddartha Naidu

CoRR, 2023

2018

Understanding disentangling in β-VAE.

Christopher P. Burgess, Irina Higgins, Arka Pal, Loïc Matthey, Nick Watters, Guillaume Desjardins, Alexander Lerchner

CoRR, 2018

SCAN: Learning Hierarchical Compositional Visual Concepts.

Irina Higgins, Nicolas Sonnerat, Loic Matthey, Arka Pal, Christopher P. Burgess, Matko Bosnjak, Murray Shanahan, Matthew M. Botvinick, Demis Hassabis, Alexander Lerchner

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

SCAN: Learning Abstract Hierarchical Compositional Visual Concepts.

Irina Higgins, Nicolas Sonnerat, Loïc Matthey, Arka Pal, Christopher P. Burgess, Matthew M. Botvinick, Demis Hassabis, Alexander Lerchner

CoRR, 2017

DARLA: Improving Zero-Shot Transfer in Reinforcement Learning.

Irina Higgins, Arka Pal, Andrei A. Rusu, Loïc Matthey, Christopher P. Burgess, Alexander Pritzel, Matthew M. Botvinick, Charles Blundell, Alexander Lerchner

Proceedings of the 34th International Conference on Machine Learning, 2017

beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework.

Irina Higgins, Loïc Matthey, Arka Pal, Christopher P. Burgess, Xavier Glorot, Matthew M. Botvinick, Shakir Mohamed, Alexander Lerchner

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Early Visual Concept Learning with Unsupervised Deep Learning.

Irina Higgins, Loïc Matthey, Xavier Glorot, Arka Pal, Benigno Uria, Charles Blundell, Shakir Mohamed, Alexander Lerchner

CoRR, 2016