245 citations · 783 across the 82 of their papers we have counts for
29 papers · 1 filter
Self Distillation Fine-Tuning of Protein Language Models Improves Versatility in Protein Design
Amin Tavakoli, Raswanth Murugan, Ozan Gokdemir +3
Supervised fine-tuning (SFT) is a standard approach for adapting large language models to specialized domains, yet its application to protein sequence modeling and protein language…
Resolution-Agnostic Neural Operators for Multi-Rate Sparse-View CT
Aujasvit Datta, Jiayun Wang, Asad Aali +1
Sparse-view Computed Tomography (CT) reconstructs images from a limited number of X-ray projections to reduce radiation and scanning time, which is an ill-posed inverse problem. Ex…
From Black Hole to Galaxy: Neural Operator: Framework for Accretion and Feedback Dynamics
Nihaal Bhojwani, Chuwei Wang, Hai-Yang Wang +3
Modeling how supermassive black holes co-evolve with their host galaxies is notoriously hard because the relevant physics spans nine orders of magnitude in scale-from milliparsecs…
Generating Natural-Language Surgical Feedback: From Structured Representation to Domain-Grounded Evaluation
Firdavs Nasriddinov, Rafal Kocielnik, Anima Anandkumar +1
High-quality intraoperative feedback from a surgical trainer is pivotal for improving trainee performance and long-term skill acquisition. Automating natural, trainer-style feedbac…
EcoSpa: Efficient Transformer Training with Coupled Sparsity
Jinqi Xiao, Cheng Luo, Lingyi Huang +8
Transformers have become the backbone of modern AI, yet their high computational demands pose critical system challenges. While sparse training offers efficiency gains, existing me…
BRIDGE: Building Representations In Domain Guided Program Synthesis
Robert Joseph George, Carson Eisenach, Udaya Ghai +3
Large language models can generate plausible code, but remain brittle for formal verification in proof assistants such as Lean. A central scalability challenge is that verified syn…