Poster Papers
24,624 papers found • Page 3 of 493
A4A: Adapter for Adapter Transfer via All-for-All Mapping for Cross-Architecture Models
Keyu Tu, Mengqi Huang, Zhuowei Chen et al.
AAAR-1.0: Assessing AI’s Potential to Assist Research
Renze Lou, Hanzi Xu, Sijia Wang et al.
AA-CLIP: Enhancing Zero-Shot Anomaly Detection via Anomaly-Aware CLIP
wenxin ma, Xu Zhang, Qingsong Yao et al.
AANet: Virtual Screening under Structural Uncertainty via Alignment and Aggregation
Wenyu Zhu, Jianhui Wang, Bowen Gao et al.
A Bayesian Approach to Contextual Dynamic Pricing using the Proportional Hazards Model with Discrete Price Data
Dongguen Kim, Young-Geun Choi, Minwoo Chae
A Bayesian Fast-Slow Framework to Mitigate Interference in Non-Stationary Reinforcement Learning
Yihuan Mao, Chongjie Zhang
A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints
Michael Munn, Susan Wei
ABBSPO: Adaptive Bounding Box Scaling and Symmetric Prior based Orientation Prediction for Detecting Aerial Image Objects
Woojin Lee, Hyugjae Chang, Jaeho Moon et al.
ABC-Former: Auxiliary Bimodal Cross-domain Transformer with Interactive Channel Attention for White Balance
Yu-Cheng Chiu, GUAN-RONG CHEN, Zihao Chen et al.
A-Bench: Are LMMs Masters at Evaluating AI-generated Images?
Zicheng Zhang, Haoning Wu, Chunyi Li et al.
A Benchmark for Semantic Sensitive Information in LLMs Outputs
Qingjie Zhang, Han Qiu, Di Wang et al.
A Beyond-Worst-Case Analysis of Greedy k-means++
Qingyun Chen, Sungjin Im, Ben Moseley et al.
A Bias-Free Training Paradigm for More General AI-generated Image Detection
Fabrizio Guillaro, Giada Zingarini, Ben Usman et al.
Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
Shengbin Ye, Meng Li
A Black-Box Debiasing Framework for Conditional Sampling
Han Cui, Jingbo Liu
A Black Swan Hypothesis: The Role of Human Irrationality in AI Safety
Hyunin Lee, Chanwoo Park, David Abel et al.
ABNet: Adaptive explicit-Barrier Net for Safe and Scalable Robot Learning
Wei Xiao, Johnson Tsun-Hsuan Wang, Chuang Gan et al.
A Bregman Proximal Viewpoint on Neural Operators
Abdel-Rahim Mezidi, Jordan Patracone, Saverio Salzo et al.
Absorb and Converge: Provable Convergence Guarantee for Absorbing Discrete Diffusion Models
Yuchen Liang, Renxiang Huang, Lifeng LAI et al.
AbstentionBench: Reasoning LLMs Fail on Unanswerable Questions
Polina Kirichenko, Mark Ibrahim, Kamalika Chaudhuri et al.
Abstract Counterfactuals for Language Model Agents
Edoardo Pona, Milad Kazemi Mehrabadi, Yali Du et al.
AC3D: Analyzing and Improving 3D Camera Control in Video Diffusion Transformers
Sherwin Bahmani, Ivan Skorokhodov, Guocheng Qian et al.
ACAM-KD: Adaptive and Cooperative Attention Masking for Knowledge Distillation
Qizhen Lan, Qing Tian
ACAttack: Adaptive Cross Attacking RGB-T Tracker via Multi-Modal Response Decoupling
Xinyu Xiang, Qinglong Yan, HAO ZHANG et al.
A Causal Lens for Learning Long-term Fair Policies
Jacob Lear, Lu Zhang
A Causal World Model Underlying Next Token Prediction: Exploring GPT in a Controlled Environment
Raanan Yehezkel Rohekar, Yaniv Gurwicz, Sungduk Yu et al.
A Cautionary Tale on Integrating Studies with Disparate Outcome Measures for Causal Inference
Harsh Parikh, Trang Nguyen, Elizabeth Stuart et al.
Acc3D: Accelerating Single Image to 3D Diffusion Models via Edge Consistency Guided Score Distillation
Kendong Liu, Zhiyu Zhu, Hui LIU et al.
ACC-Collab: An Actor-Critic Approach to Multi-Agent LLM Collaboration
Andrew Estornell, Jean-Francois Ton, Yuanshun Yao et al.
Accelerate 3D Object Detection Models via Zero-Shot Attention Key Pruning
Lizhen Xu, Xiuxiu Bai, Xiaojun Jia et al.
Accelerated Diffusion Models via Speculative Sampling
Valentin De Bortoli, Alexandre Galashov, Arthur Gretton et al.
Accelerated Distance-adaptive Methods for Hölder Smooth and Convex Optimization
Yijin Ren, Haifeng Xu, Qi Deng
Accelerated Evolving Set Processes for Local PageRank Computation
Binbin Huang, Luo Luo, Yanghua Xiao et al.
Accelerated Over-Relaxation Heavy-Ball Method: Achieving Global Accelerated Convergence with Broad Generalization
Jingrong Wei, Long Chen
Accelerated Sampling from Masked Diffusion Models via Entropy Bounded Unmasking
Heli Ben-Hamu, Itai Gat, Daniel Severo et al.
Accelerated training through iterative gradient propagation along the residual path
Erwan Fagnou, Paul Caillon, Blaise Delattre et al.
Accelerated Vertical Federated Adversarial Learning through Decoupling Layer-Wise Dependencies
Tianxing Man, Yu Bai, Ganyu Wang et al.
Accelerating 3D Molecule Generation via Jointly Geometric Optimal Transport
Haokai Hong, Wanyu LIN, KC Tan
Accelerating 3D Molecule Generative Models with Trajectory Diagnosis
Zhilong Zhang, Yuxuan Song, Yichun Wang et al.
Accelerating Auto-regressive Text-to-Image Generation with Training-free Speculative Jacobi Decoding
Yao Teng, Han Shi, Xian Liu et al.
Accelerating Block Coordinate Descent for LLM Finetuning via Landscape Expansion
Qijun Luo, Yifei Shen, Liangzu Peng et al.
Accelerating Diffusion Sampling via Exploiting Local Transition Coherence
shangwen zhu, Han Zhang, Zhantao Yang et al.
Accelerating Diffusion Transformers with Token-wise Feature Caching
Chang Zou, Xuyang Liu, Ting Liu et al.
Accelerating Diffusion Transformer via Gradient-Optimized Cache
Junxiang Qiu, Lin Liu, Shuo Wang et al.
Accelerating Diffusion Transformer via Increment-Calibrated Caching with Channel-Aware Singular Value Decomposition
Zhiyuan Chen, Keyi Li, Yifan Jia et al.
Accelerating Feature Conformal Prediction via Taylor Approximation
Zihao Tang, Boyuan Wang, Chuan Wen et al.
Accelerating Goal-Conditioned Reinforcement Learning Algorithms and Research
Michał Bortkiewicz, Władysław Pałucki, Vivek Myers et al.
Accelerating Inference of Retrieval-Augmented Generation via Sparse Context Selection
Yun Zhu, Jia-Chen Gu, Caitlin Sikora et al.
Accelerating Large Language Model Reasoning via Speculative Search
Zhihai Wang, Jie Wang, Jilai Pan et al.
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Alessandro Pierro, Steven Abreu, Jonathan Timcheck et al.