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Fernando Diaz

7 accepted papers

2026

RankList – a Listwise Preference Learning Framework for Predicting Subjective Preferences

AAAI 2026technical

Preference learning has gained significant attention in tasks involving subjective human judgments, such as speech emotion recognition (SER) and image aesthetic assessment. While pairwise frameworks such as RankNet offer robust modeling of relative preferences, they are inherently limited to local c

Cited by 0SourcePDFScholar
2025

Contextual Metric Meta-Evaluation by Measuring Local Metric Accuracy

NAACL 2025findings

Meta-evaluation of automatic evaluation metrics—assessing evaluation metrics themselves—is crucial for accurately benchmarking natural language processing systems and has implications for scientific inquiry, production model development, and policy enforcement. While existing approaches to metric me…

2025

MoR: Better Handling Diverse Queries with a Mixture of Sparse, Dense, and Human Retrievers

EMNLP 2025

Retrieval-augmented Generation (RAG) is powerful, but its effectiveness hinges on which retrievers we use and how. Different retrievers offer distinct, often complementary signals: BM25 captures lexical matches; dense retrievers, semantic similarity. Yet in practice, we typically fix a single retrie

2025

Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor

NeurIPS 2025poster

In AI research and practice, rigor remains largely understood in terms of methodological rigor---such as whether mathematical, statistical, or computational methods are correctly applied. We argue that this narrow conception of rigor has contributed to the concerns raised by the responsible AI commu…

Cited by 0SourceScholar
2024

Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval

NeurIPS 2024poster

Accurate modeling of the diverse and dynamic interests of users remains a significant challenge in the design of personalized recommender systems. Existing user modeling methods, like single-point and multi-point representations, have limitations w.r.t.\ accuracy, diversity, and adaptability. To ove…

Cited by 0SourcePDFScholar
2021

Artsheets for Art Datasets

NeurIPS 2021poster

Machine learning (ML) techniques are increasingly being employed within a variety of creative domains. For example, ML tools are being used to analyze the authenticity of artworks, to simulate artistic styles, and to augment human creative processes. While this progress has opened up new creative av…

Cited by 22SourceScholar