222 citations · 238 across the 17 of their papers we have counts for
7 papers · 1 filter
MEA: A Reward-Driven Multi-Agent System for Faithful Model Explanations
Yuyang Cheng, Raghav Kaushik Ravi, Srivarshinee Sridhar +3
Recent years have seen the employment of a plethora of machine learning (ML) models in high-stakes domains, but they remain largely opaque to the practitioners who act on their pre…
GenoMorph: Pathway-Grounded Genomic Disease Reasoning via Adaptive Latent Computation
Tanmoy Kanti Halder, Akash Ghosh, Arijit Roy +1
Large language models (LLMs) have demonstrated strong capabilities in biological reasoning; however, genomic disease inference remains largely dependent on memorized gene-disease a…
MMTClinic: Multimodal, Multilingual Time Series Question Answering and Reasoning Benchmark for Clinical Domain
Sourav Malakar, Harshit Nigam, Akash Ghosh +4
Time-series data in clinical settings is crucial for capturing dynamic changes in a patient's health over time, enabling timely diagnosis, personalized treatment, and early detecti…
ArogyaSutra: A Multi-Agent Framework for Multimodal Medical Reasoning in Indic Languages
Tanmoy Kanti Halder, Akash Ghosh, Subhadip Baidya +2
Multimodal Large Language Models (MLLMs) have shown promising reasoning capabilities in general domains, yet their performance remains limited in specialized settings such as healt…
LAARA: Layer-Aware Adaptive Rank Allocation for Parameter-Efficient Fine-Tuning
Ashutosh Tripathi, Surya Deep Singh, Pranab Sahoo +1
Low-Rank Adaptation is widely used for parameter-efficient fine-tuning, yet existing methods typically assign the same adapter rank to every transformer layer despite their heterog…
CarePilot: A Multi-Agent Framework for Long-Horizon Computer Task Automation in Healthcare
Akash Ghosh, Tajamul Ashraf, Rishu Kumar Singh +4
Multimodal agentic pipelines are transforming human-computer interaction by enabling efficient and accessible automation of complex, real-world tasks. However, recent efforts have…
CURE-Med: Curriculum-Informed Reinforcement Learning for Multilingual Medical Reasoning
Eric Onyame, Akash Ghosh, Subhadip Baidya +3
While large language models (LLMs) have shown to perform well on monolingual mathematical and commonsense reasoning, they remain unreliable for multilingual medical reasoning appli…