Research / Artificial Intelligence

Artificial Intelligence

Model capability, reasoning, verification, and evaluation research aimed at making autonomous systems more capable and more reliable.

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Dec 2025 · Research

Rahul Thomas, Arka Pal

ICLR 2026 · Oral

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

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Jul 2025 · Research

Rahul Thomas, Louai Zahran, Erica Choi, Micah Goldblum, Arka Pal

ICML 2025

Cascade: Token-Sharded Private LLM Inference

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Aug 2026 · Research

Arka Pal, Micah Goldblum, Rahul Thomas, Louai Zahran, Adam Block

NeurIPS 2026

Answering At Any Cost: Frontier LLMs Are Consequence-Insensitive

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Aug 2026 · Research

Kevin David Hayes, Arka Pal, Haosong Zhang, Tom Goldstein, Micah Goldblum

COLM 2026

Pinocchio: Estimating the Uncertainty of Black-Box Language Models

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Feb 2026 · Research

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

Privacy-Preserving Mechanisms Enable Cheap Verifiable Inference of LLMs

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Dec 2025 · Research

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

Knowing What You Know Is Not Enough: Large Language Model Confidences Don't Align With Their Actions

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Feb 2026 · Research

Rahul Thomas, Arka Pal

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

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Nov 2024 · Core

Eva Zhang, Arka Pal, Akilesh Potti, Micah Goldblum

NeurIPS 2024 Workshop

vTune: Verifiable Fine-Tuning for LLMs Through Backdooring

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Feb 2026 · Research

Rahul Thomas, Teo Kitanovski, Micah Goldblum, Arka Pal

Dynamic Delayed Tree Expansion For Improved Multi-Path Speculative Decoding

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Nov 2024 · Research

Micah Goldblum

Model and Data Watermarking

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