SOTAVerified

StrategyQA

StrategyQA aims to measure the ability of models to answer questions that require multi-step implicit reasoning.

Source: BIG-bench

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–40 of 40 papers

TitleStatusHype
Advancing Process Verification for Large Language Models via Tree-Based Preference Learning—0
Improving Attributed Text Generation of Large Language Models via Preference Learning—0
Towards Uncertainty-Aware Language Agent—0
IAG: Induction-Augmented Generation Framework for Answering Reasoning Questions—0
The ART of LLM Refinement: Ask, Refine, and Trust—0
Tailoring Self-Rationalizers with Multi-Reward DistillationCode0
Large Language Models Are Also Good Prototypical Commonsense Reasoners—0
Answering Unseen Questions With Smaller Language Models Using Rationale Generation and Dense Retrieval—0
Teaching Smaller Language Models To Generalise To Unseen Compositional QuestionsCode0
Deduction under Perturbed Evidence: Probing Student Simulation Capabilities of Large Language Models—0
Hint of Thought prompting: an explainable and zero-shot approach to reasoning tasks with LLMs—0
Self-Evaluation Guided Beam Search for Reasoning—0
Distilling Reasoning Capabilities into Smaller Language ModelsCode0
Learning to Decompose: Hypothetical Question Decomposition Based on Comparable Texts—0
Better Retrieval May Not Lead to Better Question Answering—0
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