Summary of Debating with More Persuasive Llms Leads to More Truthful Answers, by Akbir Khan et al.
Debating with More Persuasive LLMs Leads to More Truthful Answersby Akbir Khan, John Hughes, Dan…
Debating with More Persuasive LLMs Leads to More Truthful Answersby Akbir Khan, John Hughes, Dan…
GLaM: Fine-Tuning Large Language Models for Domain Knowledge Graph Alignment via Neighborhood Partitioning and Generative…
Discipline and Label: A WEIRD Genealogy and Social Theory of Data Annotationby Andrew Smart, Ding…
Efficient Models for the Detection of Hate, Abuse and Profanityby Christoph Tillmann, Aashka Trivedi, Bishwaranjan…
Self-Alignment of Large Language Models via Monopolylogue-based Social Scene Simulationby Xianghe Pang, Shuo Tang, Rui…
Jacquard V2: Refining Datasets using the Human In the Loop Data Correction Methodby Qiuhao Li,…
DiffSpeaker: Speech-Driven 3D Facial Animation with Diffusion Transformerby Zhiyuan Ma, Xiangyu Zhu, Guojun Qi, Chen…
Prompting Fairness: Artificial Intelligence as Game Playersby Jazmia HenryFirst submitted to arxiv on: 8 Feb…
InkSight: Offline-to-Online Handwriting Conversion by Learning to Read and Writeby Blagoj Mitrevski, Arina Rak, Julian…
You Only Need One Color Space: An Efficient Network for Low-light Image Enhancementby Qingsen Yan,…