LongMemEval benchmarks long-term memory in chat assistants, revealing 30% accuracy drops across sustained interactions and proposing indexing-retrieval-reading optimizations that boost performance.
Dense x retrieval: What retrieval granularity should we use?
4 Pith papers cite this work, alongside 5 external citations. Polarity classification is still indexing.
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SemChunk-C trains lightweight Ettin-based models to detect semantic chunk boundaries and assign functional categories in C-related code, matching larger LLMs on accuracy.
The paper surveys hallucination in LLMs with an innovative taxonomy, factors, detection methods, benchmarks, mitigation strategies, and open research directions.
A survey of RAG paradigms, components, benchmarks, and challenges for improving LLMs on knowledge-intensive tasks.
citing papers explorer
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LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory
LongMemEval benchmarks long-term memory in chat assistants, revealing 30% accuracy drops across sustained interactions and proposing indexing-retrieval-reading optimizations that boost performance.
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SemChunk-C: Semantic Segmentation for C Code
SemChunk-C trains lightweight Ettin-based models to detect semantic chunk boundaries and assign functional categories in C-related code, matching larger LLMs on accuracy.
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A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions
The paper surveys hallucination in LLMs with an innovative taxonomy, factors, detection methods, benchmarks, mitigation strategies, and open research directions.
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Retrieval-Augmented Generation for Large Language Models: A Survey
A survey of RAG paradigms, components, benchmarks, and challenges for improving LLMs on knowledge-intensive tasks.