Summary of Using Multimodal Foundation Models and Clustering For Improved Style Ambiguity Loss, by James Baker
Using Multimodal Foundation Models and Clustering for Improved Style Ambiguity Lossby James BakerFirst submitted to…
Using Multimodal Foundation Models and Clustering for Improved Style Ambiguity Lossby James BakerFirst submitted to…
Rethinking Transformer-based Multi-document Summarization: An Empirical Investigationby Congbo Ma, Wei Emma Zhang, Dileepa Pitawela, Haojie…
The Great AI Witch Hunt: Reviewers Perception and (Mis)Conception of Generative AI in Research Writingby…
LLM-based Frameworks for API Argument Filling in Task-Oriented Conversational Systemsby Jisoo Mok, Mohammad Kachuee, Shuyang…
Follow-Up Questions Improve Documents Generated by Large Language Modelsby Bernadette J TixFirst submitted to arxiv…
Empirical Evaluation of Public HateSpeech Datasetsby Sadar Jaf, Basel BarakatFirst submitted to arxiv on: 27…
DIM: Dynamic Integration of Multimodal Entity Linking with Large Language Modelby Shezheng Song, Shasha Li,…
ITERTL: An Iterative Framework for Fine-tuning LLMs for RTL Code Generationby Peiyang Wu, Nan Guo,…
Adaptive Draft-Verification for Efficient Large Language Model Decodingby Xukun Liu, Bowen Lei, Ruqi Zhang, Dongkuan…
The Pitfalls of Publishing in the Age of LLMs: Strange and Surprising Adventures with a…