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Arvind Narayanan

15 papers hereh-index 171.6k citations37 works total

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

author position
  • middle author4
  • last author11

Across the 15 of 15 papers where every author was matched, so the position is known.

fields
  • cs.AI6
  • cs.LG5
  • cs.CY3
  • cs.CL1
same name
  • Arvind Narayanan — 27 papers, h 54
  • Arvind Narayanan — 8 papers, h 5
  • Arvind Narayanan — 2 papers, h 14
  • Arvind Narayanan — 2 papers, h 2
  • Arvind Narayanan — 2 papers, h 3
  • Arvind Narayanan — 1 paper

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
20232026
most citedREFORMS: Reporting Standards for Machine Learning Based Science

19 citations · 69 across the 15 of their papers we have counts for

collaborators
Showing 2026 · cs.AIShow all

4 papers · 2 filters

cs.AI2026

Can AI agents conduct open-ended AI research? Early evidence from two case studies

Peter Kirgis, Sayash Kapoor, Andrew Schwartz +21

Forecasts of explosive AI progress hinge on AI agents automating AI research. But evidence on whether agents can carry out open-ended AI research is thin. Current evaluations eithe…

cs.AI2026

Life After Benchmark Saturation: A Case Study of CORE-Bench

Nitya Nadgir, Sayash Kapoor, Kangheng Liu +11

When a benchmark's accuracy saturates, it is often retired and replaced with a more challenging version. We show that this approach privileges accuracy and misses the opportunity t…

cs.AI2026

Open-World Evaluations for Measuring Frontier AI Capabilities

Sayash Kapoor, Peter Kirgis, Andrew Schwartz +15

Benchmark-based evaluation remains important for tracking frontier AI progress. But it can both overstate and understate deployed capability because it privileges tasks that can be…

cs.AI2026★ 2 cited

Towards a Science of AI Agent Reliability

Stephan Rabanser, Sayash Kapoor, Peter Kirgis +3

AI agents are increasingly deployed to execute important tasks. While rising accuracy scores on standard benchmarks suggest rapid progress, many agents still continue to fail in pr…

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