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Gaurav Pandey

IBM Research

16 papers hereh-index 7266 citations19 works total

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

author position
  • first author7
  • middle author9

Across the 16 of 16 papers where every author was matched, so the position is known.

fields
  • cs.CL8
  • cs.LG4
  • cs.IT2
  • cs.CV1
  • math.ST1
affiliations
  • IBM Research
Homepage
same name
  • Gaurav Pandey — 23 papers, h 17
  • Gaurav Pandey — 8 papers, h 1
  • Gaurav Pandey — 4 papers, h 4
  • Gaurav Pandey — 2 papers
  • Gaurav Pandey — 2 papers, h 7
  • Gaurav Pandey — 2 papers, h 2

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

activity
20122026
most citedTo go deep or wide in learning?

21 citations · 27 across the 14 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.CL2026

DKL: Decoupled Knowledge Learning for Instruction-Tuned Language Models

Kushagra Bhushan, Meghanadh Pulivarthi, Sai Krishna Reddy Sathi +7

RAG has become the de facto method for incorporating new, corpus-specific knowledge into an instruction following LLM (Instruct LLM). Although RAG-based prompting improves factual…

cs.CL2026

KItCAT: Knowledge Injection via Input Corruption for Auto-regressive Training

Meghanadh Pulivarthi, Kushagra Bhushan, Vineet Kumar +5

LLMs acquire vast amounts of knowledge during pre-training, but often lack the specialized knowledge needed to answer questions from niche sources such as manuals or technical docu…

cs.CL2026

ToolWeave: Structured Synthesis of Complex Multi-Turn Tool-Calling Dialogues

Dinesh Khandelwal, Gnana Prakash Punnavajhala, GPS Bhargav +4

Multi-turn tool calling is essential for LLMs to function as autonomous agents, yet synthesizing the training data required for these capabilities remains a fundamental challenge.…

cs.LG2026

Insertion Based Sequence Generation with Learnable Order Dynamics

Dhruvesh Patel, Benjamin Rozonoyer, Gaurav Pandey +3

Existing insertion-based masked diffusion models that generate sequences by interleaving token insertion with unmasking use fixed schedules that are not dependent on the data. For…

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