Trojan Prompt Attacks on Graph Neural Networks

Kavli Affiliate: Xiang Zhang | First 5 Authors: Minhua Lin, Zhiwei Zhang, Enyan Dai, Zongyu Wu, Yilong Wang | Summary: Graph Prompt Learning (GPL) has been introduced as a promising approach that uses prompts to adapt pre-trained GNN models to specific downstream tasks without requiring fine-tuning of the entire model. Despite the advantages of GPL, […]


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Role of dopamine in reward expectation and predictability during execution of action sequences

Kavli Affiliate: Patricia Janak | Authors: Robin Magnard, Yifeng Cheng, Joanna Zhou, Haley Province, Nathalie Thiriet, Patricia H Janak and Youna Vandaele | Summary: Reward-associated cues serve different functions depending on whether they precede or terminate action sequences. Cues that precede action sequences and signal opportunity for reward could serve as GO signals to initiate […]


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SimLayerKV: A Simple Framework for Layer-Level KV Cache Reduction

Kavli Affiliate: Wei Gao | First 5 Authors: Xuan Zhang, Cunxiao Du, Chao Du, Tianyu Pang, Wei Gao | Summary: Recent advancements in large language models (LLMs) have extended their capabilities to handle long contexts. However, increasing the number of model layers and the length of input sequences significantly escalates the memory required to store […]


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Machine-Learning Analysis of Radiative Decays to Dark Matter at the LHC

Kavli Affiliate: Marcela Carena | First 5 Authors: Ernesto Arganda, Marcela Carena, Martín de los Rios, Andres D. Perez, Duncan Rocha | Summary: The search for weakly interacting matter particles (WIMPs) is one of the main objectives of the High Luminosity Large Hadron Collider (HL-LHC). In this work we use Machine Learning (ML) techniques to […]


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The Affleck-Dine Curvaton

Kavli Affiliate: Gordan Krnjaic | First 5 Authors: Aurora Ireland, Gordan Krnjaic, Takuya Okawa, , | Summary: The Standard Model of particle physics does not explain the origin of the universe’s baryon asymmetry or its primordial fluctuations. The Affleck-Dine mechanism is a well-motivated scenario for generating the baryon asymmetry through the post-inflationary dynamics of a […]


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ORCHID: A Chinese Debate Corpus for Target-Independent Stance Detection and Argumentative Dialogue Summarization

Kavli Affiliate: Ke Wang | First 5 Authors: Xiutian Zhao, Ke Wang, Wei Peng, , | Summary: Dialogue agents have been receiving increasing attention for years, and this trend has been further boosted by the recent progress of large language models (LLMs). Stance detection and dialogue summarization are two core tasks of dialogue agents in […]


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Physical Space Proof of Bilinear Estimates and Applications to Nonlinear Dispersive Equations

Kavli Affiliate: Yi Zhou | First 5 Authors: Li Tu, Yi Zhou, , , | Summary: We give a simpler proof for the local well-posedness of the modified Korteweg-de Vries equations and modified Benjamin-Ono equation in $H^{frac{1}{4}}(mathbb{R})$ and $H^{frac{1}{2}}(mathbb{R})$, respectively. The proof is based on the Strichartz estimate, dyadic decomposition and a bilinear estimate given […]


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Connection between Non-Axisymmetric Structures and Neutral Gas Distribution in Disk Galaxies

Kavli Affiliate: Luis C. Ho | First 5 Authors: Ze-Zhong Liang, Jing Wang, Hua Gao, Luis C. Ho, E. Athanassoula | Summary: Non-axisymmetric structures, such as bars and spiral arms, are known to concentrate molecular gas and star formation in galaxy centers, actively building up the pseudo-bulges. However, a direct link between the neutral (i.e., […]


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Connection between Non-Axisymmetric Structures and Neutral Gas Distribution in Disk Galaxies

Kavli Affiliate: Jing Wang | First 5 Authors: Ze-Zhong Liang, Jing Wang, Hua Gao, Luis C. Ho, E. Athanassoula | Summary: Non-axisymmetric structures, such as bars and spiral arms, are known to concentrate molecular gas and star formation in galaxy centers, actively building up the pseudo-bulges. However, a direct link between the neutral (i.e., molecular […]


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Towards Better Performance in Incomplete LDL: Addressing Data Imbalance

Kavli Affiliate: Jing Wang | First 5 Authors: Zhiqiang Kou, Haoyuan Xuan, Jing Wang, Yuheng Jia, Xin Geng | Summary: Label Distribution Learning (LDL) is a novel machine learning paradigm that addresses the problem of label ambiguity and has found widespread applications. Obtaining complete label distributions in real-world scenarios is challenging, which has led to […]


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