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researcher

G. Yona

26 papers hereh-index 174.4k citations35 works total

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

author position
  • first author10
  • middle author6
  • last author9

Across the 25 of 26 papers where every author was matched, so the position is known.

fields
  • cs.CL12
  • cs.LG11
  • cs.CV2
  • cs.CY1
same name
  • G. Yona — 1 paper, h 21

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
20182026
most citedProbably Approximately Metric-Fair Learning

37 citations · 93 across the 25 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.CL2025★ 1 cited

SimpleQA Verified: A Reliable Factuality Benchmark to Measure Parametric Knowledge

Lukas Haas, Gal Yona, Giovanni D'Antonio +2

We introduce SimpleQA Verified, a 1,000-prompt benchmark for evaluating Large Language Model (LLM) short-form factuality based on OpenAI's SimpleQA. It addresses critical limitatio…

cs.CL2025

MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs

Gabrielle Kaili-May Liu, Gal Yona, Avi Caciularu +3

A critical component in the trustworthiness of LLMs is reliable uncertainty communication, yet LLMs often use assertive language when conveying false claims, leading to over-relian…

cs.CV2025

Neural Descriptors: Self-Supervised Learning of Robust Local Surface Descriptors Using Polynomial Patches

Gal Yona, Roy Velich, Ron Kimmel +1

Classical shape descriptors such as Heat Kernel Signature (HKS), Wave Kernel Signature (WKS), and Signature of Histograms of OrienTations (SHOT), while widely used in shape analysi…

cs.CL2025★ 9 cited

Confidence Improves Self-Consistency in LLMs

Amir Taubenfeld, Tom Sheffer, Eran Ofek +4

Self-consistency decoding enhances LLMs' performance on reasoning tasks by sampling diverse reasoning paths and selecting the most frequent answer. However, it is computationally e…

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