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R. Bhat

4 papers hereh-index 226 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • cs.AI1
  • cs.IR1
same name
  • R. Bhat — 18 papers, h 9
  • R. Bhat — 12 papers, h 8
  • R. Bhat — 6 papers, h 10
  • R. Bhat — 4 papers, h 15
  • R. Bhat — 4 papers, h 27
  • R. Bhat — 4 papers, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedGranite Embedding R2 Models

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

cs.AI2026

STAIR (STructure Aware Information Retriever): A novel dataset and LLM based retriever for document structure augmentation

Vineet Kumar, Meghanadh Pulivarthi, vishwajeet kumar +3

Retrieval Augmented Generation (RAG) is a key component for generating accurate and hallucination free answers using Large Language Models (LLMs). LLMs are improving at handling lo…

cs.IR2026

Granite Embedding Multilingual R2 Models

Parul Awasthy, Aashka Trivedi, Yushu Yang +14

We introduce the multilingual Granite Embedding R2 models, a family of encoder-based embedding models for enterprise-scale dense retrieval across 200+ languages. Extending our Engl…

cs.CL2025★ 1 cited

Granite Embedding R2 Models

Parul Awasthy, Aashka Trivedi, Yulong Li +17

We introduce the Granite Embedding R2 models, a comprehensive family of high-performance English encoder-based embedding models engineered for enterprise-scale dense retrieval appl…

cs.CL2025

Training with Pseudo-Code for Instruction Following

Prince Kumar, Rudra Murthy, Riyaz Bhat +1

Despite rapid advances in the capabilities of Large Language Models (LLMs), they continue to struggle with following relatively simple and unambiguous instructions, particularly wh…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.