Daniel Campos

About Daniel Campos

Daniel Campos, With an exceptional h-index of 14 and a recent h-index of 14 (since 2020), a distinguished researcher at University of Illinois at Urbana-Champaign, specializes in the field of NLP, AI, ML, Inference.

His recent articles reflect a diverse array of research interests and contributions to the field:

Using a Multi-Task-Trained Neural Network to Guide Interaction with a Query-Processing System via Useful Suggestions

Overview of the TREC 2023 Product Product Search Track

Compressing cross-lingual multi-task models at qualtrics

Efficient and robust web scale language model based retrieval, generation, and understanding

Keyphase extraction beyond language modeling

CAPOT: Creating Robust Dense Query Encoders using Post Training Contrastive Alignment

To asymmetry and beyond: Structured pruning of sequence to sequence models for improved inference efficiency

Noise-robust dense retrieval via contrastive alignment post training

Daniel Campos Information

University

Position

___

Citations(all)

3098

Citations(since 2020)

2941

Cited By

858

hIndex(all)

14

hIndex(since 2020)

14

i10Index(all)

14

i10Index(since 2020)

14

Email

University Profile Page

Google Scholar

Daniel Campos Skills & Research Interests

NLP

AI

ML

Inference

Top articles of Daniel Campos

Using a Multi-Task-Trained Neural Network to Guide Interaction with a Query-Processing System via Useful Suggestions

2023/12/26

Overview of the TREC 2023 Product Product Search Track

arXiv preprint arXiv:2311.07861

2023/11/14

Daniel Campos
Daniel Campos

H-Index: 8

Surya Kallumadi
Surya Kallumadi

H-Index: 6

Compressing cross-lingual multi-task models at qualtrics

Proceedings of the AAAI Conference on Artificial Intelligence

2023/9/6

Efficient and robust web scale language model based retrieval, generation, and understanding

2023/7/13

Keyphase extraction beyond language modeling

2023/5/23

CAPOT: Creating Robust Dense Query Encoders using Post Training Contrastive Alignment

arXiv preprint arXiv:2304.03401

2023/4/6

Daniel Campos
Daniel Campos

H-Index: 8

Chengxiang Zhai
Chengxiang Zhai

H-Index: 56

To asymmetry and beyond: Structured pruning of sequence to sequence models for improved inference efficiency

arXiv preprint arXiv:2304.02721

2023/4/5

Daniel Campos
Daniel Campos

H-Index: 8

Chengxiang Zhai
Chengxiang Zhai

H-Index: 56

Noise-robust dense retrieval via contrastive alignment post training

arXiv e-prints

2023/4

Daniel Campos
Daniel Campos

H-Index: 8

Chengxiang Zhai
Chengxiang Zhai

H-Index: 56

Dense Sparse Retrieval: Using Sparse Language Models for Inference Efficient Dense Retrieval

arXiv preprint arXiv:2304.00114

2023/3/31

Daniel Campos
Daniel Campos

H-Index: 8

Chengxiang Zhai
Chengxiang Zhai

H-Index: 56

Quick dense retrievers consume kale: Post training kullback leibler alignment of embeddings for asymmetrical dual encoders

arXiv preprint arXiv:2304.01016

2023/3/31

Daniel Campos
Daniel Campos

H-Index: 8

Chengxiang Zhai
Chengxiang Zhai

H-Index: 56

oBERTa: Improving Sparse Transfer Learning via improved initialization, distillation, and pruning regimes

arXiv preprint arXiv:2303.17612

2023/3/30

Sparse* BERT: Sparse Models Generalize To New tasks and Domains

arXiv preprint arXiv:2205.12452

2022/5/25

The optimal bert surgeon: Scalable and accurate second-order pruning for large language models

arXiv preprint arXiv:2203.07259

2022/3/14

Keyphrase extraction beyond language modeling

2022/2/15

Fostering coopetition while plugging leaks: The design and implementation of the MS MARCO leaderboards

2022/7/6

IMG2SMI: translating molecular structure images to simplified molecular-input line-entry system

arXiv preprint arXiv:2109.04202

2021/9/3

Daniel Campos
Daniel Campos

H-Index: 8

Heng Ji
Heng Ji

H-Index: 42

Curriculum learning for language modeling

arXiv preprint arXiv:2108.02170

2021/8/4

Daniel Campos
Daniel Campos

H-Index: 8

TREC Deep Learning Track: Reusable Test Collections in the Large Data Regime

2021/7/11

Ms marco: Benchmarking ranking models in the large-data regime

2021/7/11

Significant improvements over the state of the art? a case study of the ms marco document ranking leaderboard

2021/7/11

See List of Professors in Daniel Campos University(University of Illinois at Urbana-Champaign)

Co-Authors

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