The Utility of LLMs in Recommender Systems Explanation Evaluation
arXiv 2609.01627v1•ae84f7da8efb87338008395586b8b8a3203ac70757bcaccf85d77f2e10ffca8f
Paper metadata
- arXiv ID
- 2609.01627
- Version
- v1
- Category
- cs.AI, cs.IR
- Authors
- Kathrin Wardatzky, Oana Inel, Luca Rossetto, Abraham Bernstein
- Publication date
- 2026-09-03T04:00:00Z
- Source identifier
- 2609.01627v1
- Public record ID
- record:sha256:ae84f7da8efb87338008395586b8b8a3203ac70757bcaccf85d77f2e10ffca8f
The PDF link points to arxiv.org. Baitaphish does not expose a private stored PDF.
This is source-provided metadata, not an enriched summary or an impact assessment. Follow the canonical source link for the published material.
Evidence and limitations
- Source ID
- arxiv_research
- Record identifier
- ae84f7da8efb87338008395586b8b8a3203ac70757bcaccf85d77f2e10ffca8f
- Record type
- Source metadata
This record may overlap with other records. Source metadata can be incomplete or change. Validate consequential decisions against the linked source and your own environment.