Expectations and Practices around AI Disclosure in CS Research

arXiv:2608.23271 · cs.CY, cs.CL, cs.HC · Submitted 2026-08-24 · Read on arXiv

cs.CY, cs.CL, cs.HC

Submitted: 2026-08-24

Updated: 2026-08-25

Project page: https://ai-disclosure.github.io

Terminology

• Generative AI — 46× in this paper · explained in 2 episodes
• Large Language Model — 9× in this paper
• Large Language Models (LLMs) — 5× in this paper · explained in 6 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Accountability — 2× in this paper · explained in 2 episodes
• LLM judge — 2× in this paper · explained in 2 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Annotator Agreement — 1× in this paper · explained in 1 episode
• Artificial Intelligence Disclosure — 1× in this paper
• Benchmark — 1× in this paper · explained in 2 episodes
• Cognitive Load — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Selection Bias — 1× in this paper · explained in 4 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation
• What Shapes Writers' Decisions to Disclose AI Use?
• LLMs as Research Tools: A Large Scale Survey of Researchers' Usage and Perceptions
• Generative AI Policies under the Microscope: How CS Conferences Are Navigating the New Frontier in Scholarly Writing
• The Artificial Intelligence Disclosure (AID) Framework: An Introduction

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