Imagen de Portada

Diversity Is All You Need for Contrastive Learning: Spectral Bounds on Gradient Magnitudes

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Ochieng, Peter
Formato:	Preprint
Publicado:	2025
Materias:	Computation and Language
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Contrast Is All You Need
por: Kilic, Burak, et al.
Publicado: (2023)

Speech Separation based on Contrastive Learning and Deep Modularization
por: Ochieng, Peter
Publicado: (2023)

Is Contrasting All You Need? Contrastive Learning for the Detection and Attribution of AI-generated Text
por: La Cava, Lucio, et al.
Publicado: (2024)

Attention Is All You Need But You Don't Need All Of It For Inference of Large Language Models
por: Tyukin, Georgy, et al.
Publicado: (2024)

Not All Tokens Are What You Need In Thinking
por: Yuan, Hang, et al.
Publicado: (2025)

Increasing the Thinking Budget is Not All You Need
por: Iacobacci, Ignacio, et al.
Publicado: (2025)

Training on the Benchmark Is Not All You Need
por: Ni, Shiwen, et al.
Publicado: (2024)

Agents Are All You Need for LLM Unlearning
por: Sanyal, Debdeep, et al.
Publicado: (2025)

Speech Synthesis By Unrolling Diffusion Process using Neural Network Layers
por: Ochieng, Peter
Publicado: (2023)

More Agents Is All You Need
por: Li, Junyou, et al.
Publicado: (2024)

Arabic Text Diacritization In The Age Of Transfer Learning: Token Classification Is All You Need
por: Skiredj, Abderrahman, et al.
Publicado: (2024)

Zero-Shot Learning and Key Points Are All You Need for Automated Fact-Checking
por: Mohammadkhani, Mohammad Ghiasvand, et al.
Publicado: (2024)

Verbalized Algorithms: Classical Algorithms are All You Need (Mostly)
por: Lall, Supriya, et al.
Publicado: (2025)

Grimoire is All You Need for Enhancing Large Language Models
por: Chen, Ding, et al.
Publicado: (2024)

Addition is All You Need for Energy-efficient Language Models
por: Luo, Hongyin, et al.
Publicado: (2024)

Greed is All You Need: An Evaluation of Tokenizer Inference Methods
por: Uzan, Omri, et al.
Publicado: (2024)

Rho-1: Not All Tokens Are What You Need
por: Lin, Zhenghao, et al.
Publicado: (2024)

Predictable Emergent Abilities of LLMs: Proxy Tasks Are All You Need
por: Zhang, Bo-Wen, et al.
Publicado: (2024)

Beyond Fixed Length: Bucket Pre-training is All You Need
por: Yang, Qing, et al.
Publicado: (2024)

Selected Languages are All You Need for Cross-lingual Truthfulness Transfer
por: Liu, Weihao, et al.
Publicado: (2024)

Tensor Product Attention Is All You Need
por: Zhang, Yifan, et al.
Publicado: (2025)

Attention Smoothing Is All You Need For Unlearning
por: Zade, Saleh Zare, et al.
Publicado: (2026)

Demonstrations Are All You Need: Advancing Offensive Content Paraphrasing using In-Context Learning
por: Som, Anirudh, et al.
Publicado: (2023)

Block Rotation is All You Need for MXFP4 Quantization
por: Shao, Yuantian, et al.
Publicado: (2025)

Is Depth All You Need? An Exploration of Iterative Reasoning in LLMs
por: Wu, Zongqian, et al.
Publicado: (2025)

Is Reasoning All You Need? Probing Bias in the Age of Reasoning Language Models
por: Cantini, Riccardo, et al.
Publicado: (2025)

Is Grep All You Need? How Agent Harnesses Reshape Agentic Search
por: Sen, Sahil, et al.
Publicado: (2026)

Text Is Not All You Need: Multimodal Prompting Helps LLMs Understand Humor
por: Baluja, Ashwin
Publicado: (2024)

Reasoning Is Not All You Need: Examining LLMs for Multi-Turn Mental Health Conversations
por: Chandra, Mohit, et al.
Publicado: (2025)

Answer is All You Need: Instruction-following Text Embedding via Answering the Question
por: Peng, Letian, et al.
Publicado: (2024)

Not All Documents Are What You Need for Extracting Instruction Tuning Data
por: Zhang, Chi, et al.
Publicado: (2025)

Attention Is Not All You Need: The Importance of Feedforward Networks in Transformer Models
por: Gerber, Isaac
Publicado: (2025)

Sparsity May Be All You Need: Sparse Random Parameter Adaptation
por: Rios, Jesus, et al.
Publicado: (2025)

Self-Verification is All You Need To Pass The Japanese Bar Examination
por: Shin, Andrew
Publicado: (2026)

A Template Is All You Meme
por: Bates, Luke, et al.
Publicado: (2023)

Synthetic Data RL: Task Definition Is All You Need
por: Guo, Yiduo, et al.
Publicado: (2025)

Attention Is All You Need for KV Cache in Diffusion LLMs
por: Nguyen-Tri, Quan, et al.
Publicado: (2025)

Factuality and Transparency Are All RAG Needs! Self-Explaining Contrastive Evidence Re-ranking
por: Vargas, Francielle, et al.
Publicado: (2025)

Is Translation All You Need? A Study on Solving Multilingual Tasks with Large Language Models
por: Liu, Chaoqun, et al.
Publicado: (2024)

Don't Do RAG: When Cache-Augmented Generation is All You Need for Knowledge Tasks
por: Chan, Brian J, et al.
Publicado: (2024)