Poster Papers
24,624 papers found • Page 28 of 493
Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data
Corinna Cortes, Anqi Mao, Mehryar Mohri et al.
Balancing Two Classifiers via A Simplex ETF Structure for Model Calibration
Jiani Ni, He Zhao, Jintong Gao et al.
BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games
Davide Paglieri, Bartłomiej Cupiał, Samuel Coward et al.
BAMDP Shaping: a Unified Framework for Intrinsic Motivation and Reward Shaping
Aly Lidayan, Michael Dennis, Stuart Russell
BAME: Block-Aware Mask Evolution for Efficient N:M Sparse Training
Chenyi yang, Wenjie Nie, Yuxin Zhang et al.
BAM-ICL: Causal Hijacking In-Context Learning with Budgeted Adversarial Manipulation
Rui Chu, Bingyin Zhao, Hanling Jiang et al.
Bandit and Delayed Feedback in Online Structured Prediction
Yuki Shibukawa, Taira Tsuchiya, Shinsaku Sakaue et al.
Bandit Guided Submodular Curriculum for Adaptive Subset Selection
Prateek Chanda, Prayas Agrawal, Saral Sureka et al.
Bandit Learning in Matching Markets with Indifference
Fang Kong, Jingqi Tang, Mingzhu Li et al.
BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms
Yunlong Hou, Fengzhuo Zhang, Cunxiao Du et al.
BANet: Bilateral Aggregation Network for Mobile Stereo Matching
Gangwei Xu, Jiaxin Liu, Xianqi Wang et al.
BAnG: Bidirectional Anchored Generation for Conditional RNA Design
Roman Klypa, Alberto Bietti, Sergei Grudinin
BANGS: Game-theoretic Node Selection for Graph Self-Training
Fangxin Wang, Kay Liu, Sourav Medya et al.
Banyan: Improved Representation Learning with Explicit Structure
Mattia Opper, Siddharth N
BARD-GS: Blur-Aware Reconstruction of Dynamic Scenes via Gaussian Splatting
Yiren Lu, Yunlai Zhou, Disheng Liu et al.
BARK: A Fully Bayesian Tree Kernel for Black-box Optimization
Toby Boyne, Jose Pablo Folch, Robert Lee et al.
BASIC: Boosting Visual Alignment with Intrinsic Refined Embeddings in Multimodal Large Language Models
Jianting Tang, Yubo Wang, Haoyu Cao et al.
Basis Sharing: Cross-Layer Parameter Sharing for Large Language Model Compression
Jingcun Wang, Yu-Guang Chen, Ing-Chao Lin et al.
BASKET: A Large-Scale Video Dataset for Fine-Grained Skill Estimation
Yulu Pan, Ce Zhang, Gedas Bertasius
Batch List-Decodable Linear Regression via Higher Moments
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar et al.
BATCLIP: Bimodal Online Test-Time Adaptation for CLIP
Sarthak Kumar Maharana, Baoming Zhang, Leonid Karlinsky et al.
BaWA: Automatic Optimizing Pruning Metric for Large Language Models with Balanced Weight and Activation
Lian Liu, Xiandong Zhao, Guanchen Li et al.
Bayesian Active Learning for Bivariate Causal Discovery
Yuxuan Wang, Mingzhou Liu, Xinwei Sun et al.
Bayesian Analysis of Combinatorial Gaussian Process Bandits
Jack Sandberg, Niklas Åkerblom, Morteza Haghir Chehreghani
Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models
Mehmet Yiğit Balık, Maksim Sinelnikov, Priscilla Ong et al.
Bayesian Concept Bottleneck Models with LLM Priors
Jean Feng, Avni Kothari, Lucas Zier et al.
Bayesian Ego-graph inference for Networked Multi-Agent Reinforcement Learning
Wei Duan, Jie Lu, Junyu Xuan
Bayesian Experimental Design Via Contrastive Diffusions
Jacopo Iollo, Christophe Heinkelé, Pierre Alliez et al.
Bayesian Image Regression with Soft-thresholded Conditional Autoregressive Prior
Yuliang Xu, Jian Kang
Bayesian Inference for Correlated Human Experts and Classifiers
Markelle Kelly, Alex Boyd, Samuel Showalter et al.
Bayesian-Inspired Space-Time Superpixels
Kent Gauen, Stanley Chan
Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks
Dongwoo Lee, Dong Bok Lee, Steven Adriaensen et al.
Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
Aya Kayal, Sattar Vakili, Laura Toni et al.
Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences
Alan Amin, Nate Gruver, Yilun Kuang et al.
Bayesian Optimization via Continual Variational Last Layer Training
Paul Brunzema, Mikkel Jordahn, John Willes et al.
Bayesian Optimization with Preference Exploration using a Monotonic Neural Network Ensemble
Hanyang Wang, Juergen Branke, Matthias Poloczek
Bayesian Prompt Flow Learning for Zero-Shot Anomaly Detection
Zhen Qu, Xian Tao, Xinyi Gong et al.
Bayesian Regularization of Latent Representation
Chukwudi Paul Obite, Zhi Chang, Keyan Wu et al.
Bayesian Test-Time Adaptation for Vision-Language Models
Lihua Zhou, Mao Ye, Shuaifeng Li et al.
Bayesian Treatment of the Spectrum of the Empirical Kernel in (Sub)Linear-Width Neural Networks
Ouns El Harzli, Bernardo Grau
Bayesian WeakS-to-Strong from Text Classification to Generation
Ziyun Cui, Ziyang Zhang, Guangzhi Sun et al.
Bayesian Weight Enhancement with Steady-State Adaptation for Test-time Adaptation in Dynamic Environments
Jae-Hong Lee
Bayes optimal learning of attention-indexed models
Fabrizio Boncoraglio, Emanuele Troiani, Vittorio Erba et al.
BBCaL: Black-box Backdoor Detection under the Causality Lens
Zihan Guan, Junfeng Guo, Mengxuan Hu et al.
BCE vs. CE in Deep Feature Learning
Qiufu Li, Huibin Xiao, Linlin Shen
Be a Goldfish: Forgetting Bad Conditioning in Sparse Linear Regression via Variational Autoencoders
Kuheli Pratihar, Debdeep Mukhopadhyay
BEAST: Efficient Tokenization of B-Splines Encoded Action Sequences for Imitation Learning
Hongyi Zhou, Weiran Liao, Xi Huang et al.
BECAME: Bayesian Continual Learning with Adaptive Model Merging
Mei Li, Yuxiang Lu, Qinyan Dai et al.
BecomingLit: Relightable Gaussian Avatars with Hybrid Neural Shading
Jonathan Schmidt, Simon Giebenhain, Matthias Niessner
BEEM: Boosting Performance of Early Exit DNNs using Multi-Exit Classifiers as Experts
Divya Jyoti Bajpai, Manjesh Kumar Hanawal