Who validates the validators? aligning llm-assisted evaluation of llm outputs with human preferences

S Shankar, JD Zamfirescu-Pereira… - Proceedings of the 37th …, 2024 - dl.acm.org
Due to the cumbersome nature of human evaluation and limitations of code-based
evaluation, Large Language Models (LLMs) are increasingly being used to assist humans in …

[HTML][HTML] Large language models meet user interfaces: The case of provisioning feedback

S Pozdniakov, J Brazil, S Abdi, A Bakharia… - … and Education: Artificial …, 2024 - Elsevier
Abstract Incorporating Generative Artificial Intelligence (GenAI), especially Large Language
Models (LLMs), into educational settings presents valuable opportunities to boost the …

WeAudit: Scaffolding User Auditors and AI Practitioners in Auditing Generative AI

WH Deng, C Wang, HZ Han, JI Hong, K Holstein… - arxiv preprint arxiv …, 2025 - arxiv.org
There has been growing interest from both practitioners and researchers in engaging end
users in AI auditing, to draw upon users' unique knowledge and lived experiences …

Supporting Co-Adaptive Machine Teaching through Human Concept Learning and Cognitive Theories

SA Gebreegziabher, Y Yang, EL Glassman… - arxiv preprint arxiv …, 2024 - arxiv.org
An important challenge in interactive machine learning, particularly in subjective or
ambiguous domains, is fostering bi-directional alignment between humans and models …

SPHERE: Scaling Personalized Feedback in Programming Classrooms with Structured Review of LLM Outputs

X Tang, S Wong, M Huynh, Z He, Y Yang… - arxiv preprint arxiv …, 2024 - arxiv.org
Effective personalized feedback is crucial for learning programming. However, providing
personalized, real-time feedback in large programming classrooms poses significant …

AI-Resilient Interfaces

EL Glassman, Z Gu, JK Kummerfeld - arxiv preprint arxiv:2405.08447, 2024 - arxiv.org
AI is powerful, but it can make choices that result in objective errors, contextually
inappropriate outputs, and disliked options. We need AI-resilient interfaces that help people …

How Far Are We From AGI: Are LLMs All We Need?

T Feng, C **, J Liu, K Zhu, H Tu, Z Cheng… - … on Machine Learning …, 2024 - openreview.net
The evolution of artificial intelligence (AI) has profoundly impacted human society, driving
significant advancements in multiple sectors. Yet, the escalating demands on AI have …

VideoDiff: Human-AI Video Co-Creation with Alternatives

M Huh, D Li, K Pimmel, HV Shin, A Pavel… - arxiv preprint arxiv …, 2025 - arxiv.org
To make an engaging video, people sequence interesting moments and add visuals such as
B-rolls or text. While video editing requires time and effort, AI has recently shown strong …

Exploring Empty Spaces: Human-in-the-Loop Data Augmentation

C Yeh, D Ren, Y Assogba, D Moritz… - arxiv preprint arxiv …, 2024 - arxiv.org
Data augmentation is crucial to make machine learning models more robust and safe.
However, augmenting data can be challenging as it requires generating diverse data points …

Traceable Text: Deepening Reading of AI-Generated Summaries with Phrase-Level Provenance Links

H Kambhamettu, J Flores, A Head - arxiv preprint arxiv:2409.13099, 2024 - arxiv.org
As AI-generated summaries proliferate, how can we help people understand the veracity of
those summaries? In this short paper, we design a simple interaction primitive, traceable …