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StrategyQA

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

Source: BIG-bench

Papers

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Showing 1–10 of 40 papers

TitleStatusHype
Fusing Bidirectional Chains of Thought and Reward Mechanisms A Method for Enhancing Question-Answering Capabilities of Large Language Models for Chinese Intangible Cultural Heritage—0
Rule-Guided Feedback: Enhancing Reasoning by Enforcing Rule Adherence in Large Language Models—0
DeLTa: A Decoding Strategy based on Logit Trajectory Prediction Improves Factuality and Reasoning AbilityCode0
Voting or Consensus? Decision-Making in Multi-Agent DebateCode0
Unraveling Indirect In-Context Learning Using Influence Functions—0
AutoReason: Automatic Few-Shot Reasoning DecompositionCode1
Dialectical Behavior Therapy Approach to LLM Prompting—0
Rationale-Aware Answer Verification by Pairwise Self-EvaluationCode0
A Looming Replication Crisis in Evaluating Behavior in Language Models? Evidence and Solutions—0
Proof of Thought : Neurosymbolic Program Synthesis allows Robust and Interpretable Reasoning—0
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