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researcher

D. Agarwal

11 papers hereh-index 344.2k citations110 works total

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

author position
  • first author3
  • middle author2
  • last author5

Across the 10 of 11 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.IR2
  • stat.AP2
  • cs.CG1
  • cs.SI1
  • stat.ML1
same name
  • D. Agarwal — 80 papers, h 32
  • D. Agarwal — 23 papers, h 11
  • D. Agarwal — 6 papers, h 3
  • D. Agarwal — 5 papers, h 7
  • D. Agarwal — 3 papers, h 1
  • D. Agarwal — 2 papers, h 28

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
20052026
most citedBringing Salary Transparency to the World: Computing Robust Compensation Insights via LinkedIn Salary

10 citations · 26 across the 9 of their papers we have counts for

collaborators
Showing 2026Show all

3 papers · 1 filter

cs.LG2026

LIGE-GR: A Smooth Leap from Ranking to Generative Recommendation in the LLM Era

Venkat Srinivas, Chenzhang He, Sam Woodmansee +64

The remarkable success of large language models (LLMs) has provided important inspiration for the next generation of recommender systems. Structurally, recommendation and language…

cs.LG2026

Precision Tracked Transformer via Kalman Filtering, Kriging and Process Noise

Bo Long, Deepak Agarwal, Jelena Markovic-Voronov +2

The Transformer is the foundational building block of modern AI, yet offers no principled handling of \emph{uncertainty}, which is prevalent in real applications: cold-start tokens…

cs.LG2026

Sampling for Quality: Training-Free Reward-Guided LLM Decoding via Sequential Monte Carlo

Jelena Markovic-Voronov, Wenhui Zhu, Bo Long +5

We introduce a principled probabilistic framework for reward-guided decoding in large language models, addressing the limitations of standard decoding methods that optimize token-l…

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