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Daniel Fleischer

2 accepted papers

2025

HELMET: How to Evaluate Long-context Models Effectively and Thoroughly

ICLR 2025poster

Many benchmarks exist for evaluating long-context language models (LCLMs), yet developers often rely on synthetic tasks such as needle-in-a-haystack (NIAH) or an arbitrary subset of tasks. However, it remains unclear whether these benchmarks reflect the diverse downstream applications of LCLMs, and…

Cited by 0SourcePDFScholar
2024

CoTAR: Chain-of-Thought Attribution Reasoning with Multi-level Granularity

EMNLP 2024finding

State-of-the-art performance in QA tasks is currently achieved by systems employing Large Language Models (LLMs), however these models tend to hallucinate information in their responses. One approach focuses on enhancing the generation process by incorporating attribution from the given input to the…