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Found 4 papers, 4 papers with code
How Easily do Irrelevant Inputs Skew the Responses of Large Language Models?
By leveraging the retrieval of information from external knowledge databases, Large Language Models (LLMs) exhibit enhanced capabilities for accomplishing many knowledge-intensive tasks.
TravelPlanner: A Benchmark for Real-World Planning with Language Agents
Are these language agents capable of planning in more complex settings that are out of the reach of prior AI agents?
Deductive Beam Search: Decoding Deducible Rationale for Chain-of-Thought Reasoning
Recent advancements have significantly augmented the reasoning capabilities of Large Language Models (LLMs) through various methodologies, especially chain-of-thought (CoT) reasoning.
Towards Visual Taxonomy Expansion
Specifically, on the Chinese taxonomy dataset, our method significantly improves accuracy by 8. 75 %.
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