Publications

Please see my resume for a more up-to-date list.

Finding Transformer Circuits with Edge Pruning

Adithya Bhaskar, Alexander Wettig, Dan Friedman, and Danqi Chen

arXiv 2024

[paper] [code]

A faster and more precise circuit-finding method that also scales to multi-billion parameter models.

The Heuristic Core: Understanding Subnetwork Generalization in Pretrained Language Models

Adithya Bhaskar, Dan Friedman, and Danqi Chen

ACL 2024 (Main)

[paper] [code]

Structured pruning reveals surprising insights about how Pretrained LMs generalize.

Improving Language Understanding from Screenshots

Tianyu Gao, Zirui Wang, Adithya Bhaskar, and Danqi Chen

arXiv 2024

[paper] [code]

Multimodal Language Models can’t read well. We introduce a novel patch-and-text loss to remedy that.

Benchmarking and Improving Text-to-SQL Generation Under Ambiguity

Adithya Bhaskar*, Tushar Tomar*, Ashutosh Sathe, and Sunita Sarawagi

EMNLP 2023 (Main)

[paper] [code]

Current Text-to-SQL conversion systems fall flat on their face when faced with ambiguity. We demonstrate this by introducing a new benchmark (AmbiQT), then propose a novel method improving coverage by up to 2.5x.

Prompted Opinion Summarization with GPT-3.5

Adithya Bhaskar, Alex Fabbri and Greg Durrett

ACL 2023 (Findings)

[paper] [code]

Novel evaluation metrics for summarization in the GPT-3.5 era.

Performance Bounds for LASSO under Multiplicative Noise: Applications to Pooled RT-PCR Testing

Richeek Das, Aaron Jerry Ninan, Adithya Bhaskar and Ajit Rajwade

Signal Processing, Vol. 214, January 2024

[paper]

Performance bounds for Group Testing of, e.g., COVID-19.