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J. Ahn

4 papers hereh-index 4108 citations7 works total

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

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • cs.AI1
  • cs.CV1
same name
  • J. Ahn — 6 papers, h 12
  • J. Ahn — 3 papers, h 7
  • J. Ahn — 3 papers, h 2
  • J. Ahn — 3 papers, h 1
  • J. Ahn — 2 papers, h 18
  • J. Ahn — 2 papers, h 1

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

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2025

Prompt-Reverse Inconsistency: LLM Self-Inconsistency Beyond Generative Randomness and Prompt Paraphrasing

Jihyun Janice Ahn, Wenpeng Yin

While the inconsistency of LLMs is not a novel topic, prior research has predominantly addressed two types of generative inconsistencies: i) Randomness Inconsistency: running the s…

cs.CL2025

AAAR-1.0: Assessing AI's Potential to Assist Research

Renze Lou, Hanzi Xu, Sijia Wang +15

Numerous studies have assessed the proficiency of AI systems, particularly large language models (LLMs), in facilitating everyday tasks such as email writing, question answering, a…

cs.CL2024

Evaluating LLMs at Detecting Errors in LLM Responses

Ryo Kamoi, Sarkar Snigdha Sarathi Das, Renze Lou +12

With Large Language Models (LLMs) being widely used across various tasks, detecting errors in their responses is increasingly crucial. However, little research has been conducted o…

cs.CL2024

Direct-Inverse Prompting: Analyzing LLMs' Discriminative Capacity in Self-Improving Generation

Jihyun Janice Ahn, Ryo Kamoi, Lu Cheng +2

Mainstream LLM research has primarily focused on enhancing their generative capabilities. However, even the most advanced LLMs experience uncertainty in their outputs, often produc…

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