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Found 7 papers, 0 papers with code
zydhjh4593@SMM4H’22: A Generic Pre-trained BERT-based Framework for Social Media Health Text Classification
This paper describes our proposed framework for the 10 text classification tasks of Task 1a, 2a, 2b, 3a, 4, 5, 6, 7, 8, and 9, in the Social Media Mining for Health (SMM4H) 2022.
Estimation of Tissue Deformation and Interactive Force in Robotic Surgery through Vision-based Learning
To enhance the perception of the surgeons and precise force rendering, estimation of these forces along with tissue deformation level is presented here.
Practical Poisoning Attacks against Retrieval-Augmented Generation
Large language models (LLMs) have demonstrated impressive natural language processing abilities but face challenges such as hallucination and outdated knowledge.
CNSv2: Probabilistic Correspondence Encoded Neural Image Servo
Visual servo based on traditional image matching methods often requires accurate keypoint correspondence for high precision control.
From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities
Multi-modal Large Language Models (MLLMs) have shown impressive abilities in generating reasonable responses with respect to multi-modal contents.
DearFSAC: An Approach to Optimizing Unreliable Federated Learning via Deep Reinforcement Learning
In federated learning (FL), model aggregation has been widely adopted for data privacy.
Protum: A New Method For Prompt Tuning Based on "[MASK]"
In response to the above issue, we propose a new \textbf{Pro}mpt \textbf{Tu}ning based on "[\textbf{M}ASK]" (\textbf{Protum}) method in this paper, which constructs a classification task through the information carried by the hidden layer of "[MASK]" tokens and then predicts the labels directly rather than the answer tokens.
