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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 11–20 of 40 papers

TitleStatusHype
Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive TasksCode1
Visconde: Multi-document QA with GPT-3 and Neural RerankingCode1
Self-Consistency Improves Chain of Thought Reasoning in Language ModelsCode1
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning StrategiesCode1
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
Dialectical Behavior Therapy Approach to LLM Prompting—0
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