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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
Training Compute-Optimal Large Language ModelsCode6
Mutual Reasoning Makes Smaller LLMs Stronger Problem-SolversCode4
Scaling Language Models: Methods, Analysis & Insights from Training GopherCode2
PaLM: Scaling Language Modeling with PathwaysCode2
Escape Sky-high Cost: Early-stopping Self-Consistency for Multi-step ReasoningCode1
CR-LT-KGQA: A Knowledge Graph Question Answering Dataset Requiring Commonsense Reasoning and Long-Tail KnowledgeCode1
Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive TasksCode1
AutoReason: Automatic Few-Shot Reasoning DecompositionCode1
Distillation Contrastive Decoding: Improving LLMs Reasoning with Contrastive Decoding and DistillationCode1
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning StrategiesCode1
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