No automatic attribution scorer transfers across datasets in generated-answer attribution evaluation; per-dataset rankings invert and some drop to chance level, requiring target-dataset validation.
Asqa: Factoid questions meet long-form answers
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
dataset 2
citation-polarity summary
verdicts
UNVERDICTED 3roles
dataset 2polarities
use dataset 2representative citing papers
AdaRankLLM shows adaptive listwise reranking outperforms fixed-depth retrieval for most LLMs by acting as a noise filter for weak models and an efficiency optimizer for strong ones, with lower context use.
A survey of RAG paradigms, components, benchmarks, and challenges for improving LLMs on knowledge-intensive tasks.
citing papers explorer
-
Do LLM Attribution Metrics Transfer? Auditing Retrieval-Augmented Generation Evaluation Across Datasets and Constructs
No automatic attribution scorer transfers across datasets in generated-answer attribution evaluation; per-dataset rankings invert and some drop to chance level, requiring target-dataset validation.
-
Rethinking the Necessity of Adaptive Retrieval-Augmented Generation through the Lens of Adaptive Listwise Ranking
AdaRankLLM shows adaptive listwise reranking outperforms fixed-depth retrieval for most LLMs by acting as a noise filter for weak models and an efficiency optimizer for strong ones, with lower context use.
-
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.