21 citations · 27 across the 9 of their papers we have counts for
12 papers
Structural properties of admissible subgraphs and the depth of symbolic powers of cover ideals
Nguyen Thu Hang, Nguyen Thi Thanh Tam, Thanh Vu
Let be a simple graph with cover ideal in a polynomial ring $S = \k[x_1, \ldots, x_n]$. For each integer , let denote the maximum size of an ordered ma…
SteerDuplex: Steerable Duplex Speech Dialogue Models
Utkarsh Tyagi, Ramaneswaran Selvakumar, Advait Gosai +13
Full-duplex spoken dialogue models support low-latency turn taking, interruption handling, and backchanneling, yet a key capability remains underexplored: steerability, the ability…
Rubric-Guided Self-Distillation: Post-Training Without Rubric Verifiers
MohammadHossein Rezaei, Anas Mahmoud, Zihao Wang +6
Rubrics have emerged as an alternative to RLVR in open-ended domains where a single ground-truth final answer is not available. Existing rubric-based training methods rely on an LL…
Audio MultiChallenge: A Multi-Turn Evaluation of Spoken Dialogue Systems on Natural Human Interaction
Advait Gosai, Tyler Vuong, Utkarsh Tyagi +8
End-to-end (E2E) spoken dialogue systems are increasingly replacing cascaded pipelines for voice-based human-AI interaction, processing raw audio directly without intermediate tran…
PRBench: Large-Scale Expert Rubrics for Evaluating High-Stakes Professional Reasoning
Afra Feyza Akyürek, Advait Gosai, Chen Bo Calvin Zhang +21
Frontier model progress is often measured by academic benchmarks, which offer a limited view of performance in real-world professional contexts. Existing evaluations often fail to…
Beyond Seeing: Evaluating Multimodal LLMs on Tool-Enabled Image Perception, Transformation, and Reasoning
Xingang Guo, Utkarsh Tyagi, Advait Gosai +8
Multimodal Large Language Models (MLLMs) are increasingly applied in real-world scenarios where user-provided images are often imperfect, requiring active image manipulations such…
Scaling Laws for Neural Material Models
Akshay Trikha, Kyle Chu, Advait Gosai +2
Predicting material properties is crucial for designing better batteries, semiconductors, and medical devices. Deep learning helps scientists quickly find promising materials by pr…
Beyond Diagnosis: Evaluating Multimodal LLMs for Pathology Localization in Chest Radiographs
Advait Gosai, Arun Kavishwar, Stephanie L. McNamara +4
Recent work has shown promising performance of frontier large language models (LLMs) and their multimodal counterparts in medical quizzes and diagnostic tasks, highlighting their p…
Automated Ensemble-Based Segmentation of Adult Brain Tumors: A Novel Approach Using the BraTS AFRICA Challenge Data
Chiranjeewee Prasad Koirala, Sovesh Mohapatra, Advait Gosai +1
Brain tumors, particularly glioblastoma, continue to challenge medical diagnostics and treatments globally. This paper explores the application of deep learning to multi-modality m…
Automated ensemble method for pediatric brain tumor segmentation
Shashidhar Reddy Javaji, Sovesh Mohapatra, Advait Gosai +1
Brain tumors remain a critical global health challenge, necessitating advancements in diagnostic techniques and treatment methodologies. A tumor or its recurrence often needs to be…
Meta-Analysis of Transfer Learning for Segmentation of Brain Lesions
Sovesh Mohapatra, Advait Gosai, Anant Shinde +3
A major challenge in stroke research and stroke recovery predictions is the determination of a stroke lesion's extent and its impact on relevant brain systems. Manual segmentation…
SAM vs BET: A Comparative Study for Brain Extraction and Segmentation of Magnetic Resonance Images using Deep Learning
Sovesh Mohapatra, Advait Gosai, Gottfried Schlaug
Brain extraction is a critical preprocessing step in various neuroimaging studies, particularly enabling accurate separation of brain from non-brain tissue and segmentation of rele…