Summary of Adversarial Robustness Of In-context Learning in Transformers For Linear Regression, by Usman Anwar et al.
Adversarial Robustness of In-Context Learning in Transformers for Linear Regressionby Usman Anwar, Johannes Von Oswald,…
Summary of Can Custom Models Learn In-context? An Exploration Of Hybrid Architecture Performance on In-context Learning Tasks, by Ryan Campbell et al.
Can Custom Models Learn In-Context? An Exploration of Hybrid Architecture Performance on In-Context Learning Tasksby…
Summary of Customized Multiple Clustering Via Multi-modal Subspace Proxy Learning, by Jiawei Yao et al.
Customized Multiple Clustering via Multi-Modal Subspace Proxy Learningby Jiawei Yao, Qi Qian, Juhua HuFirst submitted…
Summary of Enhancing Transformer Training Efficiency with Dynamic Dropout, by Hanrui Yan et al.
Enhancing Transformer Training Efficiency with Dynamic Dropoutby Hanrui Yan, Dan ShaoFirst submitted to arxiv on:…
Summary of Seq-vcr: Preventing Collapse in Intermediate Transformer Representations For Enhanced Reasoning, by Md Rifat Arefin et al.
Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoningby Md Rifat Arefin, Gopeshh Subbaraj,…
Summary of Enriching Tabular Data with Contextual Llm Embeddings: a Comprehensive Ablation Study For Ensemble Classifiers, by Gjergji Kasneci and Enkelejda Kasneci
Enriching Tabular Data with Contextual LLM Embeddings: A Comprehensive Ablation Study for Ensemble Classifiersby Gjergji…
Summary of Uniguard: Towards Universal Safety Guardrails For Jailbreak Attacks on Multimodal Large Language Models, by Sejoon Oh et al.
UniGuard: Towards Universal Safety Guardrails for Jailbreak Attacks on Multimodal Large Language Modelsby Sejoon Oh,…
Summary of Can Large Language Model Predict Employee Attrition?, by Xiaoye Ma et al.
Can Large Language Model Predict Employee Attrition?by Xiaoye Ma, Weiheng Liu, Changyi Zhao, Liliya R.…
Summary of Enhancing Neural Network Interpretability with Feature-aligned Sparse Autoencoders, by Luke Marks et al.
Enhancing Neural Network Interpretability with Feature-Aligned Sparse Autoencodersby Luke Marks, Alasdair Paren, David Krueger, Fazl…
Summary of Attackqa: Development and Adoption Of a Dataset For Assisting Cybersecurity Operations Using Fine-tuned and Open-source Llms, by Varun Badrinath Krishna
AttackQA: Development and Adoption of a Dataset for Assisting Cybersecurity Operations using Fine-tuned and Open-Source…