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Richard Ren

University of Pennsylvania

10 papers hereh-index 91.7k citations13 works total

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

author position
  • first author2
  • middle author6

Across the 8 of 10 papers where every author was matched, so the position is known.

fields
  • cs.LG7
  • cs.AI2
  • cs.RO1
affiliations
  • University of Pennsylvania
  • Center for AI Safety
same name
  • Richard Ren — 1 paper, h 0

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
20212026
most citedRepresentation Engineering: A Top-Down Approach to AI Transparency

65 citations · 97 across the 8 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.LG2025★ 3 cited

Remote Labor Index: Measuring AI Automation of Remote Work

Mantas Mazeika, Alice Gatti, Cristina Menghini +44

AIs have made rapid progress on research-oriented benchmarks of knowledge and reasoning, but it remains unclear how these gains translate into economic value and automation. To mea…

cs.LG2025★ 1 cited

The MASK Benchmark: Disentangling Honesty From Accuracy in AI Systems

Richard Ren, Arunim Agarwal, Mantas Mazeika +13

As large language models (LLMs) become more capable and agentic, the requirement for trust in their outputs grows significantly, yet at the same time concerns have been mounting th…

cs.LG2025

Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs

Mantas Mazeika, Xuwang Yin, Rishub Tamirisa +8

As AIs rapidly advance and become more agentic, the risk they pose is governed not only by their capabilities but increasingly by their propensities, including goals and values. Tr…

cs.LG2025★ 23 cited

Humanity's Last Exam

Long Phan, Alice Gatti, Ziwen Han +1168

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…

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