collaborators

7 papers

cs.LG2026

Parameter-Efficient Token Embedding Editing for Clinical Class-Level Unlearning

Iyad Ait Hou, Shrenik Borad, Harsh Sharma +3

Machine unlearning is increasingly important for clinical language models, where privacy regulations and institutional policies may require removing sensitive information from depl…

cs.AI2026

FiMI: A Domain-Specific Language Model for Indian Finance Ecosystem

Aboli Kathar, Aman Kumar, Anusha Kamath +37

We present FiMI (Finance Model for India), a domain-specialized financial language model developed by National Payments Corporation of India (NPCI) for Indian digital payment syste…

cs.CL2025

NVIDIA Nemotron 3: Efficient and Open Intelligence

NVIDIA, :, Aaron Blakeman +356

We introduce the Nemotron 3 family of models - Nano, Super, and Ultra. These models deliver strong agentic, reasoning, and conversational capabilities. The Nemotron 3 family uses a…

cs.CL2025

Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning

NVIDIA, :, Aaron Blakeman +311

We present Nemotron 3 Nano 30B-A3B, a Mixture-of-Experts hybrid Mamba-Transformer language model. Nemotron 3 Nano was pretrained on 25 trillion text tokens, including more than 3 t…

cs.CL2025

From Facts to Conclusions : Integrating Deductive Reasoning in Retrieval-Augmented LLMs

Shubham Mishra, Samyek Jain, Gorang Mehrishi +4

Retrieval-Augmented Generation (RAG) grounds large language models (LLMs) in external evidence, but fails when retrieved sources conflict or contain outdated or subjective informat…

cs.CL2025

NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model

NVIDIA, :, Aarti Basant +214

We introduce Nemotron-Nano-9B-v2, a hybrid Mamba-Transformer language model designed to increase throughput for reasoning workloads while achieving state-of-the-art accuracy compar…