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20232026
most citedChain-of-Verification Reduces Hallucination in Large Language Models

42 citations · 55 across the 17 of their papers we have counts for

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7 papers · 1 filter

cs.AI2026

Agent Plasticity: Measuring Self-Improvement Through Experience

Harman Singh, Anton Bakhtin, Rulin Shao +8

AI agents increasingly operate in environments where they can diagnose failures and improve through experience, yet existing evaluations largely measure what an agent can do at a f…

cs.AI2026

GitSwarm: Decentralized Compounding Inference

Vedant Shah, Ankur Samanta, Paras Dahal +11

Long-horizon problem solving and scientific research require computation to accumulate across successive attempts. Partial solutions, experimental findings, and unsuccessful approa…

cs.AI2026

Thinking Before Thinking: Scaling Agentic Inference Through Meta-Reasoning

Paras Dahal, Anton Bakhtin, Taco Cohen +9

As agents take on longer and more complex problems, controlling the execution becomes a task in its own right. Each step in the run brings new control choices, like which partial w…

cs.AI2026

AI Research Preference Models

Thomas Simon Foster, Bassel Al Omari, Tingchen Fu +30

AI research agents (AIRA) can now carry machine learning experiments from proposal through implementation and evaluation. Yet progress on frontier tasks is throttled by the cost of…

cs.AI2026

Autodata: An agentic data scientist to create high quality synthetic data

Ilia Kulikov, Chenxi Whitehouse, Tianhao Wu +12

We introduce Autodata, a general method that enables AI agents to act as data scientists who build high quality training and evaluation data. We show how to train (meta-optimize) s…

cs.AI2026

Reasoning over mathematical objects: on-policy reward modeling and test time aggregation

Pranjal Aggarwal, Marjan Ghazvininejad, Seungone Kim +18

The ability to precisely derive mathematical objects is a core requirement for downstream STEM applications, including mathematics, physics, and chemistry, where reasoning must cul…

cs.CL2026

CharacterFlywheel: Scaling Iterative Improvement of Engaging and Steerable LLMs in Production

Yixin Nie, Lin Guan, Zhongyao Ma +19

This report presents CharacterFlywheel, an iterative flywheel process for improving large language models (LLMs) in production social chat applications across Instagram, WhatsApp,…