Poster Papers
24,624 papers found • Page 16 of 493
Conference
An Adaptive Quantum Circuit of Dempster's Rule of Combination for Uncertain Pattern Classification
Fuyuan Xiao, Yu Zhou, Witold Pedrycz
ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning
Nilo Schwencke, Cyril Furtlehner
An All-Atom Generative Model for Designing Protein Complexes
Ruizhe Chen, Dongyu Xue, Xiangxin Zhou et al.
Analog Foundation Models
Julian Büchel, Iason Chalas, Giovanni Acampa et al.
AnalogGenie: A Generative Engine for Automatic Discovery of Analog Circuit Topologies
Jian Gao, Weidong Cao, Junyi Yang et al.
AnalogGenie-Lite: Enhancing Scalability and Precision in Circuit Topology Discovery through Lightweight Graph Modeling
Jian Gao, Weidong Cao, Xuan Zhang
Analogy-based Multi-Turn Jailbreak against Large Language Models
Mengjie Wu, Yihao Huang, Zhenjun Lin et al.
Analysing The Spectral Biases in Generative Models
Amitoj Miglani, Shweta Singh, Vidit Aggarwal
Analysis of Linear Mode Connectivity via Permutation-Based Weight Matching: With Insights into Other Permutation Search Methods
Akira Ito, Masanori Yamada, Atsutoshi Kumagai
Analytical Lyapunov Function Discovery: An RL-based Generative Approach
Haohan Zou, Jie Feng, Hao Zhao et al.
Analytic Energy-Guided Policy Optimization for Offline Reinforcement Learning
Jifeng Hu, Sili Huang, Zhejian Yang et al.
Analyze Feature Flow to Enhance Interpretation and Steering in Language Models
Daniil Laptev, Nikita Balagansky, Yaroslav Aksenov et al.
Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language Models
Hulingxiao He, Geng Li, Zijun Geng et al.
Analyzing Fine-Grained Alignment and Enhancing Vision Understanding in Multimodal Language Models
Jiachen Jiang, Jinxin Zhou, Bo Peng et al.
Analyzing Finetuning Representation Shift for Multimodal LLMs Steering
Pegah KHAYATAN, Mustafa Shukor, Jayneel Parekh et al.
Analyzing Neural Scaling Laws in Two-Layer Networks with Power-Law Data Spectra
Roman Worschech, Bernd Rosenow
Analyzing Similarity Metrics for Data Selection for Language Model Pretraining
Dylan Sam, Ayan Chakrabarti, Afshin Rostamizadeh et al.
Analyzing the Power of Chain of Thought through Memorization Capabilities
Lijia Yu, Xiao-Shan Gao, Lijun Zhang
Analyzing the Synthetic-to-Real Domain Gap in 3D Hand Pose Estimation
Zhuoran ZHAO, Linlin Yang, Pengzhan Sun et al.
An Analysis of Concept Bottleneck Models: Measuring, Understanding, and Mitigating the Impact of Noisy Annotations
Seonghwan Park, Jueun Mun, Donghyun Oh et al.
An Architecture Search Framework for Inference-Time Techniques
Jon Saad-Falcon, Adrian Lafuente, Shlok Natarajan et al.
An Asymptotically Optimal Approximation Algorithm for Multiobjective Submodular Maximization at Scale
Fabian Spaeh, Atsushi Miyauchi
An Asynchronous Bundle Method for Distributed Learning Problems
Daniel Cederberg, Xuyang Wu, Stephen Boyd et al.
Anatomical Consistency and Adaptive Prior-informed Transformation for Multi-contrast MR Image Synthesis via Diffusion Model
Yejee Shin, Yeeun Lee, Hanbyol Jang et al.
Anatomically inspired digital twins capture hierarchical object representations in visual cortex
Emanuele Luconi, Dario Liscai, Carlo Baldassi et al.
An Augmentation-Aware Theory for Self-Supervised Contrastive Learning
Jingyi Cui, Hongwei Wen, Yisen Wang
Anchor-Aware Similarity Cohesion in Target Frames Enables Predicting Temporal Moment Boundaries in 2D
Jiawei Tan, Hongxing Wang, Junwu Weng et al.
Anchor-based Maximum Discrepancy for Relative Similarity Testing
Zhijian Zhou, Liuhua Peng, Xunye Tian et al.
Anchored Diffusion Language Model
Litu Rout, Constantine Caramanis, Sanjay Shakkottai
Anchor Token Matching: Implicit Structure Locking for Training-free AR Image Editing
Taihang Hu, Linxuan Li, Kai Wang et al.
AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents
Chris Rawles, Sarah Clinckemaillie, Yifan Chang et al.
A Near Linear Query Lower Bound for Submodular Maximization
Binghui Peng, Aviad Rubinstein
A Near-optimal, Scalable and Parallelizable Framework for Stochastic Bandits Robust to Adversarial Corruptions and Beyond
Zicheng Hu, Cheng Chen
A Near-Optimal Single-Loop Stochastic Algorithm for Convex Finite-Sum Coupled Compositional Optimization
Bokun Wang, Tianbao Yang
An Effective and Secure Federated Multi-View Clustering Method with Information-Theoretic Perspective
Xinyue Chen, Jinfeng Peng, Yuhao Li et al.
An Effective Levelling Paradigm for Unlabeled Scenarios
Fangming Cui, Zhou Yu, Di Yang et al.
An Effective Manifold-based Optimization Method for Distributionally Robust Classification
Jiawei Huang, Hu Ding
An Effective Theory of Bias Amplification
Arjun Subramonian, Samuel Bell, Levent Sagun et al.
An Efficient Framework for Crediting Data Contributors of Diffusion Models
MingYu Lu, Chris Lin, Chanwoo Kim et al.
An Efficient Hybrid Vision Transformer for TinyML Applications
Fanhong Zeng, Huanan LI, Juntao Guan et al.
An Efficient Local Search Approach for Polarized Community Discovery in Signed Networks
Linus Aronsson, Morteza Haghir Chehreghani
An Efficient Matrix Multiplication Algorithm for Accelerating Inference in Binary and Ternary Neural Networks
Mohsen Dehghankar, Mahdi Erfanian, Abolfazl Asudeh
An Efficient Post-hoc Framework for Reducing Task Discrepancy of Text Encoders for Composed Image Retrieval
Jaeseok Byun, Seokhyeon Jeong, Wonjae Kim et al.
An Efficient Private GPT Never Autoregressively Decodes
Zhengyi Li, Yue Guan, Kang Yang et al.
An Efficient Pruner for Large Language Model with Theoretical Guarantee
Canhong Wen, Yihong Zuo, Wenliang Pan
An Efficient Search-and-Score Algorithm for Ancestral Graphs using Multivariate Information Scores for Complex Non-linear and Categorical Data
Nikita Lagrange, Herve Isambert
An Ellipsoid Algorithm for Online Convex Optimization
Zakaria Mhammedi
An Empirical Analysis of Uncertainty in Large Language Model Evaluations
Qiujie Xie, Qingqiu Li, Zhuohao Yu et al.
An Empirical Study of Autoregressive Pre-training from Videos
Jathushan Rajasegaran, Ilija Radosavovic, Rahul Ravishankar et al.
An Empirical Study on Configuring In-Context Learning Demonstrations for Unleashing MLLMs' Sentimental Perception Capability
Daiqing Wu, Dongbao Yang, Sicheng Zhao et al.