Constraints in Generalization Structures in Conceptual Database Schemes. - Marcela Varas; A. Ricardo Contreras; Daniel Campos (SCCC, 1998)

Satellite-Indoor Mobile Communications Path Propagation Losses. - Daniel Campos; Luis Gerardo Guerrero-Ojeda; Vicente Alarcón Aquino; David Báez-López (CONIELECOMP, 2006)

Improving BCI-based emotion recognition by combining EEG feature selection and kernel classifiers. - John Atkinson 001; Daniel Campos (Expert Syst. Appl., 2016)

Systems of Interaction between the First Sedentary Villages in the Near East Exposed Using Agent-Based Modelling of Obsidian Exchange. - David Ortega; Juan-José Ibáñez; Daniel Campos; Lamya Khalidi; Vicenç Méndez; Luís Teira (Syst., 2016)

Open Domain Web Keyphrase Extraction Beyond Language Modeling. - Lee Xiong; Chuan Hu; Chenyan Xiong; Daniel Campos; Arnold Overwijk (EMNLP/IJCNLP (1), 2019)

Experiments in Inferring Social Networks of Diffusion. - Daniel Campos; Zoe Konrad (CoRR, 2019)

ORCAS: 20 Million Clicked Query-Document Pairs for Analyzing Search. - Nick Craswell; Daniel Campos; Bhaskar Mitra 001; Emine Yilmaz; Bodo Billerbeck (CIKM, 2020)

XGLUE: A New Benchmark Datasetfor Cross-lingual Pre-training, Understanding and Generation. - Yaobo Liang; Nan Duan; Yeyun Gong; Ning Wu; Fenfei Guo; Weizhen Qi; Ming Gong 001; Linjun Shou; Daxin Jiang; Guihong Cao; Xiaodong Fan; Ruofei Zhang; et al. (EMNLP (1), 2020)

On the Reliability of Test Collections for Evaluating Systems of Different Types. - Emine Yilmaz; Nick Craswell; Bhaskar Mitra 001; Daniel Campos (SIGIR, 2020)

Overview of the TREC 2020 Deep Learning Track. - Nick Craswell; Bhaskar Mitra 001; Emine Yilmaz; Daniel Campos (TREC, 2020)

Leading Conversational Search by Suggesting Useful Questions. - Corbin Rosset; Chenyan Xiong; Xia Song; Daniel Campos; Nick Craswell; Saurabh Tiwary; Paul N. Bennett (WWW, 2020)

Overview of the TREC 2019 deep learning track. - Nick Craswell; Bhaskar Mitra 001; Emine Yilmaz; Daniel Campos; Ellen M. Voorhees (CoRR, 2020)

ORCAS: 18 Million Clicked Query-Document Pairs for Analyzing Search. - Nick Craswell; Daniel Campos; Bhaskar Mitra 001; Emine Yilmaz; Bodo Billerbeck (CoRR, 2020)

MS MARCO: Benchmarking Ranking Models in the Large-Data Regime. - Nick Craswell; Bhaskar Mitra 001; Emine Yilmaz; Daniel Campos; Jimmy Lin (SIGIR, 2021)

TREC Deep Learning Track: Reusable Test Collections in the Large Data Regime. - Nick Craswell; Bhaskar Mitra 001; Emine Yilmaz; Daniel Campos; Ellen M. Voorhees; Ian Soboroff (SIGIR, 2021)

Significant Improvements over the State of the Art? A Case Study of the MS MARCO Document Ranking Leaderboard. - Jimmy Lin; Daniel Campos; Nick Craswell; Bhaskar Mitra 001; Emine Yilmaz (SIGIR, 2021)

Overview of the TREC 2021 Deep Learning Track. - Nick Craswell; Bhaskar Mitra 001; Emine Yilmaz; Daniel Campos; Jimmy Lin (TREC, 2021)

Towards Labeling On-Demand IoT Traffic. - Daniel Campos; T. J. OConnor (CSET @ USENIX Security Symposium, 2021)

Through the Spyglass: Towards IoT Companion App Man-in-the-Middle Attacks. - T. J. OConnor; Dylan Jessee; Daniel Campos (CSET @ USENIX Security Symposium, 2021)

Curriculum learning for language modeling. - Daniel Campos (CoRR, 2021)

IMG2SMI: Translating Molecular Structure Images to Simplified Molecular-input Line-entry System. - Daniel Campos; Heng Ji (CoRR, 2021)

The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models. - Eldar Kurtic; Daniel Campos; Tuan Nguyen; Elias Frantar; Mark Kurtz; Benjamin Fineran; Michael Goin; Dan Alistarh (EMNLP, 2022)

Fostering Coopetition While Plugging Leaks: The Design and Implementation of the MS MARCO Leaderboards. - Jimmy Lin; Daniel Campos; Nick Craswell; Bhaskar Mitra 001; Emine Yilmaz (SIGIR, 2022)

Overview of the TREC 2022 Deep Learning Track. - Nick Craswell; Bhaskar Mitra 001; Emine Yilmaz; Daniel Campos; Jimmy Lin; Ellen M. Voorhees; Ian Soboroff (TREC, 2022)

Sparse*BERT: Sparse Models are Robust. - Daniel Campos; Alexandre Noll Marques; Tuan Nguyen; Mark Kurtz; ChengXiang Zhai (CoRR, 2022)

Informational Entropy Threshold as a Physical Mechanism for Explaining Tree-like Decision Making in Humans. - Javier Cristín; Vicenç Méndez; Daniel Campos (Entropy, 2022)

Compressing Cross-Lingual Multi-Task Models at Qualtrics. - Daniel Campos; Daniel J. Perry; Samir Joshi; Yashmeet Gambhir; Wei Du; Zhengzheng Xing; Aaron Colak (AAAI, 2023)

Towards Examining The Security Cost of Inexpensive Smart Home IoT Devices. - T. J. OConnor; Dylan Jessee; Daniel Campos (COMPSAC, 2023)

oBERTa: Improving Sparse Transfer Learning via improved initialization, distillation, and pruning regimes. - Daniel Campos; Alexandre Noll Marques; Mark Kurtz; ChengXiang Zhai (SustaiNLP, 2023)

Quick Dense Retrievers Consume KALE: Post Training KullbackLeibler Alignment of Embeddings for Asymmetrical dual encoders. - Daniel Campos; Alessandro Magnani; Chengxiang Zhai (SustaiNLP, 2023)

To Asymmetry and Beyond: Structured Pruning of Sequence to Sequence Models for Improved Inference Efficiency. - Daniel Campos; Chengxiang Zhai (SustaiNLP, 2023)

OVERVIEW OF THE TREC 2023 PRODUCT PRODUCT SEARCH TRACK. - Daniel Campos; Surya Kallumadi; Corby Rosset; Cheng Xiang Zhai; Alessandro Magnani (TREC, 2023)

Overview of the TREC 2023 Deep Learning Track. - Nick Craswell; Bhaskar Mitra 001; Emine Yilmaz; Hossein A. Rahmani; Daniel Campos; Jimmy Lin; Ellen M. Voorhees; Ian Soboroff (TREC, 2023)

Dense Sparse Retrieval: Using Sparse Language Models for Inference Efficient Dense Retrieval. - Daniel Campos; ChengXiang Zhai (CoRR, 2023)

Quick Dense Retrievers Consume KALE: Post Training Kullback Leibler Alignment of Embeddings for Asymmetrical dual encoders. - Daniel Campos; Alessandro Magnani; ChengXiang Zhai (CoRR, 2023)

Noise-Robust Dense Retrieval via Contrastive Alignment Post Training. - Daniel Campos; ChengXiang Zhai; Alessandro Magnani (CoRR, 2023)

Synthetic Test Collections for Retrieval Evaluation. - Hossein A. Rahmani; Nick Craswell; Emine Yilmaz; Bhaskar Mitra 001; Daniel Campos (SIGIR, 2024)

Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models. - Luke Merrick; Danmei Xu; Gaurav Nuti; Daniel Campos (CoRR, 2024)

Managing O-RAN Networks: xApp Development from Zero to Hero. - Joao F. Santos; Alexandre Huff; Daniel Campos; Kleber Vieira Cardoso; Cristiano Bonato Both; Luiz A. DaSilva (CoRR, 2024)

A Large-Scale Study of Relevance Assessments with Large Language Models: An Initial Look. - Shivani Upadhyay; Ronak Pradeep; Nandan Thakur; Daniel Campos; Nick Craswell; Ian Soboroff; Hoa Trang Dang; Jimmy Lin (CoRR, 2024)

Initial Nugget Evaluation Results for the TREC 2024 RAG Track with the AutoNuggetizer Framework. - Ronak Pradeep; Nandan Thakur; Shivani Upadhyay; Daniel Campos; Nick Craswell; Jimmy Lin (CoRR, 2024)

Arctic-Embed 2.0: Multilingual Retrieval Without Compromise. - Puxuan Yu; Luke Merrick; Gaurav Nuti; Daniel Campos (CoRR, 2024)

ColBERT-Serve: Efficient Multi-stage Memory-Mapped Scoring. - Kaili Huang; Thejas Venkatesh; Uma Dingankar; Antonio Mallia; Daniel Campos; Jian Jiao; Christopher Potts; Matei Zaharia; Kwabena Boahen 001; Omar Khattab; Saarthak Sarup; Keshav Santhanam (ECIR (4), 2025)

Ragnarök: A Reusable RAG Framework and Baselines for TREC 2024 Retrieval-Augmented Generation Track. - Ronak Pradeep; Nandan Thakur; Sahel Sharifymoghaddam; Eric Zhang; Ryan Nguyen; Daniel Campos; Nick Craswell; Jimmy Lin (ECIR (1), 2025)

The Great Nugget Recall: Automating Fact Extraction and RAG Evaluation with Large Language Models. - Ronak Pradeep; Nandan Thakur; Shivani Upadhyay; Daniel Campos; Nick Craswell; Ian Soboroff; Hoa Trang Dang; Jimmy Lin (SIGIR, 2025)

Assessing Support for the TREC 2024 RAG Track: A Large-Scale Comparative Study of LLM and Human Evaluations. - Nandan Thakur; Ronak Pradeep; Shivani Upadhyay; Daniel Campos; Nick Craswell; Ian Soboroff; Hoa Trang Dang; Jimmy Lin (SIGIR, 2025)

The Great Nugget Recall: Automating Fact Extraction and RAG Evaluation with Large Language Models. - Ronak Pradeep; Nandan Thakur; Shivani Upadhyay; Daniel Campos; Nick Craswell; Jimmy Lin (CoRR, 2025)

Support Evaluation for the TREC 2024 RAG Track: Comparing Human versus LLM Judges. - Nandan Thakur; Ronak Pradeep; Shivani Upadhyay; Daniel Campos; Nick Craswell; Jimmy Lin (CoRR, 2025)

EnronQA: Towards Personalized RAG over Private Documents. - Michael J. Ryan; Danmei Xu; Chris Nivera; Daniel Campos (CoRR, 2025)