Papers with Gemini-1.5-Flash

2 papers
CAPE: Context-Aware Personality Evaluation Framework for Large Language Models (2025.findings-emnlp)

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Challenge: Existing studies use a context-free approach to assess humans . existing studies use the Disney World test, which ignores real-world applications .
Approach: They propose a framework to assess personality traits in large language models . they use conversational history to quantify the consistency of LLM responses .
Outcome: The proposed framework improves consistency of responses in large language models . it also shows that conversational history enhances consistency and personality shifts .
UniRAG: A Unified RAG Framework for Knowledge-Intensive Queries with Decomposition, Break-Down Reasoning, and Iterative Rewriting (2025.findings-emnlp)

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Challenge: Existing retrieval-augmented generation approaches struggle with query complexity, propagated reasoning errors, or rely on incomplete or noisy retrieval.
Approach: a unified retrieval-augmented generation framework is developed to address query complexity . the framework decomposes queries into semantically coherent sub-queries . it explicitly verifies retrieved sub-facts and adaptively refines queries based on identified knowledge gaps.
Outcome: a new framework improves answer completeness and reliability by decomposing queries into coherent sub-queries . the framework explicitly verifies retrieved sub-facts and adaptively refines queries based on identified knowledge gaps.

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