activity
20242026
most citedTowards Large Reasoning Models for Agriculture

1 citations · 1 across the 3 of their papers we have counts for

collaborators

7 papers

cs.AI2026

Estimation of Propagated Risk in LLM-based Multi-Agent Systems

Shreyan Ganguly, Souradeep Chattopadhyay, Qisai Liu +1

Large Language Model (LLM) based multi-agent systems introduce a distinctive reliability challenge in which actions taken by upstream agents can affect the correctness of downstrea…

cs.CV2026

Seeing Seizures: A Large-Scale Empirical Study of Video and EEG Deep Learning for Automated Rodent Seizure Detection and Severity Grading

Alloy Das, Shreyan Ganguly, Nyzil Massey +4

Manual annotation of synchronized video and EEG recordings is a bottleneck in preclinical seizure research. We present an empirical study of seizure detection and behavioral severi…

cs.CV2025

In-Context Adaptation of VLMs for Few-Shot Cell Detection in Optical Microscopy

Shreyan Ganguly, Angona Biswas, Jaydeep Rade +9

Foundation vision-language models (VLMs) excel on natural images, but their utility for biomedical microscopy remains underexplored. In this paper, we investigate how in-context le…

cs.RO2025

Can Pretrained Vision-Language Embeddings Alone Guide Robot Navigation?

Nitesh Subedi, Adam Haroon, Shreyan Ganguly +4

Foundation models have revolutionized robotics by providing rich semantic representations without task-specific training. While many approaches integrate pretrained vision-language…

cs.LG2025★ 1 cited

Towards Large Reasoning Models for Agriculture

Hossein Zaremehrjerdi, Shreyan Ganguly, Ashlyn Rairdin +17

Agricultural decision-making involves complex, context-specific reasoning, where choices about crops, practices, and interventions depend heavily on geographic, climatic, and econo…

cs.LG2025

DeCAF: Decentralized Consensus-And-Factorization for Low-Rank Adaptation of Foundation Models

Nastaran Saadati, Zhanhong Jiang, Joshua R. Waite +4

Low-Rank Adaptation (LoRA) has emerged as one of the most effective, computationally tractable fine-tuning approaches for training Vision-Language Models (VLMs) and Large Language…

cs.LG2024

AdaKD: Dynamic Knowledge Distillation of ASR models using Adaptive Loss Weighting

Shreyan Ganguly, Roshan Nayak, Rakshith Rao +2

Knowledge distillation, a widely used model compression technique, works on the basis of transferring knowledge from a cumbersome teacher model to a lightweight student model. The…