Summary of Allam: Large Language Models For Arabic and English, by M Saiful Bari et al.
ALLaM: Large Language Models for Arabic and Englishby M Saiful Bari, Yazeed Alnumay, Norah A.…
Summary of Scaling Granite Code Models to 128k Context, by Matt Stallone et al.
Scaling Granite Code Models to 128K Contextby Matt Stallone, Vaibhav Saxena, Leonid Karlinsky, Bridget McGinn,…
Summary of Interpretability in Action: Exploratory Analysis Of Vpt, a Minecraft Agent, by Karolis Jucys et al.
Interpretability in Action: Exploratory Analysis of VPT, a Minecraft Agentby Karolis Jucys, George Adamopoulos, Mehrab…
Summary of Ideal: Leveraging Infinite and Dynamic Characterizations Of Large Language Models For Query-focused Summarization, by Jie Cao et al.
IDEAL: Leveraging Infinite and Dynamic Characterizations of Large Language Models for Query-focused Summarizationby Jie Cao,…
Summary of Vimi: Grounding Video Generation Through Multi-modal Instruction, by Yuwei Fang et al.
VIMI: Grounding Video Generation through Multi-modal Instructionby Yuwei Fang, Willi Menapace, Aliaksandr Siarohin, Tsai-Shien Chen,…
Summary of From Loops to Oops: Fallback Behaviors Of Language Models Under Uncertainty, by Maor Ivgi et al.
From Loops to Oops: Fallback Behaviors of Language Models Under Uncertaintyby Maor Ivgi, Ori Yoran,…
Summary of On the Evaluation Practices in Multilingual Nlp: Can Machine Translation Offer An Alternative to Human Translations?, by Rochelle Choenni et al.
On the Evaluation Practices in Multilingual NLP: Can Machine Translation Offer an Alternative to Human…
Summary of Infusing Clinical Knowledge Into Tokenisers For Language Models, by Abul Hasan et al.
Infusing clinical knowledge into tokenisers for language modelsby Abul Hasan, Jinge Wu, Quang Ngoc Nguyen,…
Summary of A Pure Transformer Pretraining Framework on Text-attributed Graphs, by Yu Song et al.
A Pure Transformer Pretraining Framework on Text-attributed Graphsby Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe…
Summary of Llms Are Prone to Fallacies in Causal Inference, by Nitish Joshi et al.
LLMs Are Prone to Fallacies in Causal Inferenceby Nitish Joshi, Abulhair Saparov, Yixin Wang, He…