59 citations · 162 across the 62 of their papers we have counts for
43 papers · 1 filter
Verify to Amplify: Improving Reasoning via Learned Chain-of-Thought Verification
Maria-Florina Balcan, Avrim Blum, Kiriaki Fragkia +2
Large Language Models (LLMs) using chain-of-thought have demonstrated great potential for solving complex reasoning and planning tasks. Despite these advances, LLM-generated output…
Algorithm Design and Stronger Guarantees for the Improving Multi-Armed Bandits Problem
Avrim Blum, Marten Garicano, Kavya Ravichandran +1
The improving multi-armed bandits problem is a formal model for allocating effort under uncertainty, motivated by scenarios such as investing research effort into new technologies,…
Prior Knowledge Makes It Possible: From Sublinear Graph Algorithms to LLM Test-Time Methods
Avrim Blum, Daniel Hsu, Cyrus Rashtchian +1
Test-time augmentation, such as Retrieval-Augmented Generation (RAG) or tool use, critically depends on an interplay between a model's parametric knowledge and externally retrieved…
Strategic Filtering for Content Moderation: Free Speech or Free of Distortion?
Saba Ahmadi, Avrim Blum, Haifeng Xu +1
User-generated content (UGC) on social media platforms is vulnerable to incitements and manipulations, necessitating effective regulations. To address these challenges, those platf…
A Machine Learning Theory Perspective on Strategic Litigation
Melissa Dutz, Han Shao, Avrim Blum +1
Strategic litigation involves bringing a case to court with the goal of having an impact beyond resolving the particular dispute at hand. In a common law system, one way a case may…
On Learning Verifiers and Implications to Chain-of-Thought Reasoning
Maria-Florina Balcan, Avrim Blum, Zhiyuan Li +1
Chain-of-Thought reasoning has emerged as a powerful approach for solving complex mathematical and logical problems. However, it can often veer off track through incorrect or unsub…