Image de couverture de livre

Pushing Toward the Simplex Vertices: A Simple Remedy for Code Collapse in Smoothed Vector Quantization

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Morita, Takashi
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Representation Collapsing Problems in Vector Quantization
par: Zhao, Wenhao, et autres
Publié: (2024)

A Simplex Witness Certificate for Constant Collapse in Variational Autoencoders
par: Zhang, Zegu, et autres
Publié: (2026)

Vector Quantization in the Brain: Grid-like Codes in World Models
par: Peng, Xiangyuan, et autres
Publié: (2025)

Pushing the Limits of Block Rotations in Post-Training Quantization
par: Sanjeet, Sai, et autres
Publié: (2026)

VP-VAE: Rethinking Vector Quantization via Adaptive Vector Perturbation
par: Zhai, Linwei, et autres
Publié: (2026)

RWKVQuant: Quantizing the RWKV Family with Proxy Guided Hybrid of Scalar and Vector Quantization
par: Xu, Chen, et autres
Publié: (2025)

4bit-Quantization in Vector-Embedding for RAG
par: Jeong, Taehee
Publié: (2025)

Rank Collapse Causes Over-Smoothing and Over-Correlation in Graph Neural Networks
par: Roth, Andreas, et autres
Publié: (2023)

GPTQT: Quantize Large Language Models Twice to Push the Efficiency
par: Guo, Yipin, et autres
Publié: (2024)

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
par: Huang, Wei, et autres
Publié: (2024)

LLMs Judging LLMs: A Simplex Perspective
par: Vossler, Patrick, et autres
Publié: (2025)

ASER: Activation Smoothing and Error Reconstruction for Large Language Model Quantization
par: Zhao, Weibo, et autres
Publié: (2024)

Early Quantization Shrinks Codebook: A Simple Fix for Diversity-Preserving Tokenization
par: Zhao, Wenhao, et autres
Publié: (2026)

Fast and Simplex: 2-Simplicial Attention in Triton
par: Roy, Aurko, et autres
Publié: (2025)

Simple Baselines are Competitive with Code Evolution
par: Gideoni, Yonatan, et autres
Publié: (2026)

Smoothness Really Matters: A Simple Yet Effective Approach for Unsupervised Graph Domain Adaptation
par: Chen, Wei, et autres
Publié: (2024)

Learning Grouped Lattice Vector Quantizers for Low-Bit LLM Compression
par: Zhang, Xi, et autres
Publié: (2025)

Divide et Calibra: Multiclass Local Calibration via Vector Quantization
par: Barbera, Cesare, et autres
Publié: (2026)

VQ-SAD: Vector Quantized Structure Aware Diffusion For Molecule Generation
par: Noravesh, Farshad, et autres
Publié: (2026)

Mitigating Adversarial Perturbations for Deep Reinforcement Learning via Vector Quantization
par: Luu, Tung M., et autres
Publié: (2024)

SmaAT-QMix-UNet: A Parameter-Efficient Vector-Quantized UNet for Precipitation Nowcasting
par: Stavrou, Nikolas, et autres
Publié: (2026)

PTQ1.61: Push the Real Limit of Extremely Low-Bit Post-Training Quantization Methods for Large Language Models
par: Zhao, Jiaqi, et autres
Publié: (2025)

Graph is a Natural Regularization: Revisiting Vector Quantization for Graph Representation Learning
par: Zhai, Zian, et autres
Publié: (2025)

Incorporating Exponential Smoothing into MLP: A Simple but Effective Sequence Model
par: Chu, Jiqun, et autres
Publié: (2024)

Towards Realistic Guarantees: A Probabilistic Certificate for SmoothLLM
par: Kumarappan, Adarsh, et autres
Publié: (2025)

Simplex-enabled Safe Continual Learning Machine
par: Cao, Hongpeng, et autres
Publié: (2024)

PCDVQ: Enhancing Vector Quantization for Large Language Models via Polar Coordinate Decoupling
par: Yue, Yuxuan, et autres
Publié: (2025)

MaxSup: Overcoming Representation Collapse in Label Smoothing
par: Zhou, Yuxuan, et autres
Publié: (2025)

NSNQuant: A Double Normalization Approach for Calibration-Free Low-Bit Vector Quantization of KV Cache
par: Son, Donghyun, et autres
Publié: (2025)

FoldToken: Learning Protein Language via Vector Quantization and Beyond
par: Gao, Zhangyang, et autres
Publié: (2024)

ICQuant: Index Coding enables Low-bit LLM Quantization
par: Li, Xinlin, et autres
Publié: (2025)

Towards Superior Quantization Accuracy: A Layer-sensitive Approach
par: Zhang, Feng, et autres
Publié: (2025)

CodeGEMM: A Codebook-Centric Approach to Efficient GEMM in Quantized LLMs
par: Park, Gunho, et autres
Publié: (2025)

BeamVQ: Beam Search with Vector Quantization to Mitigate Data Scarcity in Physical Spatiotemporal Forecasting
par: Wang, Weiyan, et autres
Publié: (2025)

Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting
par: Zhao, Yanjun, et autres
Publié: (2024)

STORM: A Spatio-Temporal Factor Model Based on Dual Vector Quantized Variational Autoencoders for Financial Trading
par: Zhao, Yilei, et autres
Publié: (2024)

Smooth InfoMax -- Towards Easier Post-Hoc Interpretability
par: Denoodt, Fabian, et autres
Publié: (2024)

RQ-MoE: Residual Quantization via Mixture of Experts for Efficient Input-Dependent Vector Compression
par: Zhong, Zhengjia, et autres
Publié: (2026)

VQSynery: Robust Drug Synergy Prediction With Vector Quantization Mechanism
par: Wu, Jiawei, et autres
Publié: (2024)

From Signal Degradation to Computation Collapse: Uncovering the Two Failure Modes of LLM Quantization
par: Zhou, Chenxi, et autres
Publié: (2026)