Raghuveer Thirukovalluru | Duke University

About Me

I am a 4-th year Ph.D. student at Duke University. I am very fortunate to be advised by Prof. Bhuwan Dhingra. Prior to starting my PhD, I was a masters student at UMass Amherst where I worked on amazing projects with IESL. I spent four amazing years of my undergrad at IIT Kanpur.

After my undergrad I spent 2 years at Xerox Research working on some text and graph problems. Over the years, I’ve intered at multiple places including MetaAI, XRCI, IESL.

Research Interests

My research in Machine Learning for Natural Language Processing (NLP) focuses on enhancing performance of Large Language Models. I’ve worked on integrating knowledge graphs to improve reasoning in question-answering, optimizing coreference resolution efficiency. Currently, I’m interested in adaptively applying inference-time compute to improve long-form generation, embeddings, and other tasks.

News

[Nov. 2024] Will be presenting ‘Atomic Self-Consistency’ at EMNLP 2024. Come say hi!!.
[Oct. 2024] New prepreint on training-free embeddings on arXiv. Checkout GenEOL.
[June. 2024] Presented ‘Summary Transformation for Contrastive Learning’ at NAACL.
[May. 2024] Presented ‘Sequence Reducible Holdout Loss for LM Pretraining’ at COLING.
[Apr. 2024] Presented ‘Atomic Self-Consistency’ at the SouthNLPSymposium (Oral).

Publications

Preprint

GenEOL: Harnessing the Generative Power of LLMs for Training-Free Sentence Embeddings

Raghuveer Thirukovalluru, Bhuwan Dhingra

arXiv

PDF Code
EMNLP

Atomic Self-Consistency for Better Long Form Generations

Raghuveer Thirukovalluru, Yukun Huang, Bhuwan Dhingra

In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024)

PDF Code Oral at SouthNLPSymposium 2024
NAACL

SumCSE: Summary as a transformation for Contrastive Learning

Raghuveer Thirukovalluru, Xiaolan Wang, Jun Chen, Shuyang Li, Jie Lei, Rong Jin, Bhuwan Dhingra

In Findings of the Association for Computational Linguistics (NAACL 2024)

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COLING

Sequence Reducible Holdout Loss for Language Model Pretraining

Raghuveer Thirukovalluru, Nicholas Monath, Bhuwan Dhingra, Sam Wiseman

In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

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RepL4NLP

Knowledge Informed Semantic Parsing for Conversational Question Answering

Raghuveer Thirukovalluru*, Mukund Sridhar*, Dung Thai*, Shruti Chanumolu, Nicholas Monath, Sankaranarayanan Ananthakrishnan, Andrew McCallum (*Equal Author)

Workshop on Representation Learning for NLP (RepL4NLP-2021).

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RepL4NLP

Simultaneously self-attending to text and entities for knowledge-informed text representations

Dung Thai*, Raghuveer Thirukovalluru*, Trapit Bansal*, Andrew McCallum (*Equal Author)

Workshop on Representation Learning for NLP (RepL4NLP-2021).

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ACL

Scaling within document coreference to long texts.

Raghuveer Thirukovalluru, Nicholas Monath, Kumar Shridhar, Manzil Zaheer, Mrinmaya Sachan, and Andrew McCallum.

Findings of the Association for Computational Linguistics, ACL-IJCNLP 2021 (2021)

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Reviewing

Neurips 2023, AAAI 2024, ICML 2023, ICML 2024
ARR - Dec’23, Feb’24, June’24, August’24

Beyond the Code

I love hiking. I've visited 8 national parks.
Chess enthusiast, 1700+ rapid on Chess.com. Challenge me [here]!
Passionate about ping-pong and badminton. Just let me know when!