Summary of Token Prepending: a Training-free Approach For Eliciting Better Sentence Embeddings From Llms, by Yuchen Fu et al.
Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMsby Yuchen Fu, Zifeng…
Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMsby Yuchen Fu, Zifeng…
Dual Traits in Probabilistic Reasoning of Large Language Modelsby Shenxiong Li, Huaxia RuiFirst submitted to…
CATER: Leveraging LLM to Pioneer a Multidimensional, Reference-Independent Paradigm in Translation Quality Evaluationby Kurando IIDA,…
Just a Few Glances: Open-Set Visual Perception with Image Prompt Paradigmby Jinrong Zhang, Penghui Wang,…
Rethinking Chain-of-Thought from the Perspective of Self-Trainingby Zongqian Wu, Baoduo Xu, Ruochen Cui, Mengmeng Zhan,…
Active Inference for Self-Organizing Multi-LLM Systems: A Bayesian Thermodynamic Approach to Adaptationby Rithvik PrakkiFirst submitted…
GPTDrawer: Enhancing Visual Synthesis through ChatGPTby Kun Li, Xinwei Chen, Tianyou Song, Hansong Zhang, Wenzhe…
How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narrativesby Timour Ichmoukhamedov,…
CP-DETR: Concept Prompt Guide DETR Toward Stronger Universal Object Detectionby Qibo Chen, Weizhong Jin, Jianyue…
Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Clinical Pathology Analysisby Shengxuming Zhang,…