Fernando Diaz
Associate Professor
Studies information retrieval and recommendation, including evaluation and fairness of search systems.
Fernando Diaz's lab at CMU works on interpretability, evaluation & safety of LMs, knowledge, QA & retrieval and recommendation, search & web. 30 papers since 2023, 13 at top venues, mostly SIGIR and NeurIPS. Applications close .
At a glance
- papers, 2023–2026
- 8/ year
- at T1 venues
- 43%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 8 papers2026 · T1 6 · collecting
- 8 papers2025 · T1 4
- 11 papers2024 · T1 2
- 3 papers2023 · T1 1
T1 venuesOtherVenues: SIGIR, NeurIPS, AAAI/ACM AIES, AAAI, CSCW
Research focuspaper titles that use each topic's words
- Interpretability, evaluation & safety of LMs11 papers
- Knowledge, QA & retrieval3 papers
- Recommendation, search & web1 paper
- recommendation1 paper
- studies information0 papers
Paper list
From the lab homepage.
20268 papers
- AAAI/ACM AIES"I want to be pushed, I want to grow": Enabling social workers to design evaluations of LLM augmentation in their work (opens in a new tab)
- C3NLPCharacterizing Cultural Localization in AI-Generated Stories (opens in a new tab)
- WSDM (T1)Diversification as Risk Minimization (opens in a new tab)
- SIGIR (T1)Evaluation of Agents under Simulated AI Marketplace Dynamics (opens in a new tab)
- SIGIR (T1)LTRR: Learning To Rank Retrievers for LLMs (opens in a new tab)
- SIGIR (T1)Multilingual and Domain-Agnostic Tip-of-the-Tongue Query Generation for Simulated Evaluation (opens in a new tab)
- NeurIPS (T1)Offline Preference-Based Trajectory Evaluation (opens in a new tab)
- AAAI (T1)RankList -- A Listwise Preference Learning Framework for Predicting Subjective Preferences (opens in a new tab)
20258 papers
- NAACL (T1)Contextual Metric Meta-Evaluation by Measuring Local Metric Accuracy (opens in a new tab)
- EMNLP (T1)MoR: Better Handling Diverse Queries with a Mixture of Sparse, Dense, and Human Retrievers (opens in a new tab)
- TRECOverview of the TREC 2025 Tip-of-the-Tongue track (opens in a new tab)
- ACM Transactions on Recommender Systems, FebruaryRecall, Robustness, and Lexicographic Evaluation (opens in a new tab)
- NeurIPS (T1)Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor (opens in a new tab)
- SIGIR (T1)Tip of the Tongue Query Elicitation for Simulated Evaluation (opens in a new tab)
- Dagstuhl ReportsTowards a Multidisciplinary Vision for Culturally Inclusive Generative AI (opens in a new tab)
- ICTIRTowards Fair RAG: On the Impact of Fair Ranking in Retrieval-Augmented Generation (opens in a new tab)
202411 papers
- Knight First Amendment Institute, JulyA Public Service Media Perspective on the Algorithmic Amplification of Cultural Content (opens in a new tab)
- NeurIPS (T1)Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval (opens in a new tab)
- ACM Transactions on Recommender Systems, MarchDistributionally-Informed Recommender System Evaluation (opens in a new tab)
- Findings of EMNLPExtrinsic Evaluation of Cultural Competence in Large Language Models (opens in a new tab)
- ECIRFairness Through Domain Awareness: Mitigating Popularity Bias For Music Discovery (opens in a new tab)
- ACM Transactions on Recommender Systems, MarchMeasuring Commonality in Recommendation of Cultural Content to Strengthen Cultural Citizenship (opens in a new tab)
- SIGIR-APOffline Evaluation of Set-Based Text-to-Image Generation (opens in a new tab)
- TRECOverview of the TREC 2024 Tip-of-the-Tongue track (opens in a new tab)
- SIGIR-APPessimistic Evaluation (opens in a new tab)
- AAAI/ACM AIESScaling Laws Do Not Scale (opens in a new tab)
- SIGIR (T1)The Impact of Group Membership Bias on the Quality and Fairness of Exposure in Ranking (opens in a new tab)
20233 papers
- CSCW (T1)AI Consent Futures: A Case Study on Voice Data Collection with Clinicians (opens in a new tab)
- EVIABest-Case Retrieval Evaluation: Improving the Sensitivity of Reciprocal Rank with Lexicographic Precision (opens in a new tab)
- TRECOverview of the TREC 2023 Tip-of-the-Tongue track (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to CMUFall 2027
CMU SCS Computer Science PhD
- Round
- Single round
- Opens
- GRE
- See program page
- English
- TOEFL / IELTS / Duolingo (F-1/J-1 non-native speakers)
- Fee
- USD 100 (USD 80 by early deadline)
Confirmed on the program page.
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Data
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- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
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- The lab homepage
- Members
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- Alumni
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