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cs.CL2026
GRAFITE: Generative Regression Analysis Framework for Issue Tracking and Evaluation
Ja Young Lee, Mírian Silva, Mohamed Nasr +6
Large language models (LLMs) are largely motivated by their performance on popular topics and benchmarks at the time of their release. However, over time, contamination occurs due…
cs.CL2026★ 1 cited
MTRAG-UN: A Benchmark for Open Challenges in Multi-Turn RAG Conversations
Sara Rosenthal, Yannis Katsis, Vraj Shah +3
We present MTRAG-UN, a benchmark for exploring open challenges in multi-turn retrieval augmented generation, a popular use of large language models. We release a benchmark of 666 t…