Summary of Unveiling Selection Biases: Exploring Order and Token Sensitivity in Large Language Models, by Sheng-lun Wei et al.
Unveiling Selection Biases: Exploring Order and Token Sensitivity in Large Language Modelsby Sheng-Lun Wei, Cheng-Kuang…
Summary of Fedmkt: Federated Mutual Knowledge Transfer For Large and Small Language Models, by Tao Fan et al.
FedMKT: Federated Mutual Knowledge Transfer for Large and Small Language Modelsby Tao Fan, Guoqiang Ma,…
Summary of Code: Contrasting Self-generated Description to Combat Hallucination in Large Multi-modal Models, by Junho Kim et al.
CODE: Contrasting Self-generated Description to Combat Hallucination in Large Multi-modal Modelsby Junho Kim, Hyunjun Kim,…
Summary of Focus on the Core: Efficient Attention Via Pruned Token Compression For Document Classification, by Jungmin Yun et al.
Focus on the Core: Efficient Attention via Pruned Token Compression for Document Classificationby Jungmin Yun,…
Summary of Mlip: Efficient Multi-perspective Language-image Pretraining with Exhaustive Data Utilization, by Yu Zhang et al.
MLIP: Efficient Multi-Perspective Language-Image Pretraining with Exhaustive Data Utilizationby Yu Zhang, Qi Zhang, Zixuan Gong,…
Summary of Focus: Forging Originality Through Contrastive Use in Self-plagiarism For Language Models, by Kaixin Lan et al.
FOCUS: Forging Originality through Contrastive Use in Self-Plagiarism for Language Modelsby Kaixin Lan, Tao Fang,…
Summary of A Theory For Token-level Harmonization in Retrieval-augmented Generation, by Shicheng Xu et al.
A Theory for Token-Level Harmonization in Retrieval-Augmented Generationby Shicheng Xu, Liang Pang, Huawei Shen, Xueqi…
Summary of Clustered Retrieved Augmented Generation (crag), by Simon Akesson and Frances A. Santos
Clustered Retrieved Augmented Generation (CRAG)by Simon Akesson, Frances A. SantosFirst submitted to arxiv on: 24…
Summary of Diffusion on Syntax Trees For Program Synthesis, by Shreyas Kapur et al.
Diffusion On Syntax Trees For Program Synthesisby Shreyas Kapur, Erik Jenner, Stuart RussellFirst submitted to…
Summary of Contextual Position Encoding: Learning to Count What’s Important, by Olga Golovneva et al.
Contextual Position Encoding: Learning to Count What’s Importantby Olga Golovneva, Tianlu Wang, Jason Weston, Sainbayar…