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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 1–25 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
Mutual Reasoning Makes Smaller LLMs Stronger Problem-SolversCode4
Meta-prompting Optimized Retrieval-augmented Generation—0
Question-Analysis Prompting Improves LLM Performance in Reasoning Tasks—0
Advancing Process Verification for Large Language Models via Tree-Based Preference Learning—0
Unchosen Experts Can Contribute Too: Unleashing MoE Models' Power by Self-ContrastCode1
Improving Attributed Text Generation of Large Language Models via Preference Learning—0
CR-LT-KGQA: A Knowledge Graph Question Answering Dataset Requiring Commonsense Reasoning and Long-Tail KnowledgeCode1
Distillation Contrastive Decoding: Improving LLMs Reasoning with Contrastive Decoding and DistillationCode1
Towards Uncertainty-Aware Language Agent—0
Escape Sky-high Cost: Early-stopping Self-Consistency for Multi-step ReasoningCode1
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
Improving Planning with Large Language Models: A Modular Agentic ArchitectureCode1
Large Language Models Are Also Good Prototypical Commonsense Reasoners—0
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