Papers
Grokking Beyond the Euclidean Norm of Model Parameters
Tikeng Notsawo Pascal Junior, Guillaume Dumas, Guillaume Rabusseau
Grokking in the Wild: Data Augmentation for Real-World Multi-Hop Reasoning with Transformers
Roman Abramov, Felix Steinbauer, Gjergji Kasneci
GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs
Yue Wang, Qizhou Wang, Feng Liu et al.
GS-Bias: Global-Spatial Bias Learner for Single-Image Test-Time Adaptation of Vision-Language Models
Zhaohong Huang, Yuxin Zhang, Jingjing Xie et al.
G-Sim: Generative Simulations with Large Language Models and Gradient-Free Calibration
Samuel Holt, Max Ruiz Luyten, Antonin Berthon et al.
GSM-$∞$: How Do your LLMs Behave over Infinitely Increasing Reasoning Complexity and Context Length?
Yang Zhou, Hongyi Liu, Zhuoming Chen et al.
GTR: A General, Multi-View, and Dynamic Framework for Trajectory Representation Learning
Xiangheng Wang, Ziquan Fang, Chenglong Huang et al.
Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery
Paris Giampouras, Hanqin Cai, Rene Vidal
GuardAgent: Safeguard LLM Agents via Knowledge-Enabled Reasoning
Zhen Xiang, Linzhi Zheng, Yanjie Li et al.
Guardians of Image Quality: Benchmarking Defenses Against Adversarial Attacks on Image Quality Metrics
Aleksandr Gushchin, Khaled Abud, Georgii Bychkov et al.
GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance
Jinuk Kim, Marwa El Halabi, Wonpyo Park et al.
Guided Search Strategies in Non-Serializable Environments with Applications to Software Engineering Agents
Karina Zainullina, Alexander Golubev, Maria Trofimova et al.
Guided Structural Inference: Leveraging Priors with Soft Gating Mechanisms
Aoran Wang, Xinnan Dai, Jun Pang
Guided Zeroth-Order Methods for Stochastic Non-convex Problems with Decision-Dependent Distributions
Yuya Hikima, Hiroshi Sawada, Akinori Fujino
Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding
Jinze Li, Yixing Xu, Haiduo Huang et al.
Habitizing Diffusion Planning for Efficient and Effective Decision Making
Haofei Lu, Yifei Shen, Dongsheng Li et al.
HALoS: Hierarchical Asynchronous Local SGD over Slow Networks for Geo-Distributed Large Language Model Training
Geon-Woo Kim, Junbo Li, Shashidhar Gandham et al.
Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin
Yuchen Wang, Xuefeng Bai, Xiucheng Li et al.
HaploVL: A Single-Transformer Baseline for Multi-Modal Understanding
Rui Yang, Lin Song, Yicheng Xiao et al.
Hardware and Software Platform Inference
Cheng Zhang, Hanna Foerster, Robert D. Mullins et al.
HarmoniCa: Harmonizing Training and Inference for Better Feature Caching in Diffusion Transformer Acceleration
Yushi Huang, Zining Wang, Ruihao Gong et al.
Harmonizing Geometry and Uncertainty: Diffusion with Hyperspheres
Muskan Dosi, Chiranjeev Chiranjeev, Kartik Thakral et al.
HashAttention: Semantic Sparsity for Faster Inference
Aditya Desai, Shuo Yang, Alejandro Cuadron et al.
Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks
Rui Xue, Tong Zhao, Neil Shah et al.