Papers with GPQA datasets

2 papers
Budget-Aware Anytime Reasoning with LLM-Synthesized Preference Data (2026.findings-acl)

Copied to clipboard

Challenge: Recent work has explored reasoning efficiency via test-time scaling and early exit strategies.
Approach: They propose an anytime reasoning framework and the Anytime Index to improve model quality . they also propose an inference-time self-improvement method to produce better intermediate solutions .
Outcome: The proposed method improves on NaturalPlan, AIME, and GPQA datasets and improves reasoning quality and efficiency under budget constraints.
Do Language Models Mirror Human Confidence? Exploring Psychological Insights to Address Overconfidence in LLMs (2025.findings-acl)

Copied to clipboard

Challenge: Psychology research has shown that humans are poor at estimating their performance on tasks, tending towards underconfidence on easy tasks and overconfidence on difficult tasks.
Approach: They propose to use a self-assessment method to assess confidence in large language models (LLMs) they propose to ask for the answer separately and then use them to improve their accuracy.
Outcome: The proposed method improves confidence calibration and interpretability in QA tasks with different personas.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations