Copertina

Telogenesis: Goal Is All U Need

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Deng, Zhuoran, Zhang, Yizhi, Zhang, Ziyi, Shen, Wan
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Mamba or Transformer for Time Series Forecasting? Mixture of Universals (MoU) Is All You Need
di: Peng, Sijia, et al.
Pubblicazione: (2024)

Training Multimodal Large Reasoning Models Needs Better Thoughts: A Three-Stage Framework for Long Chain-of-Thought Synthesis and Selection
di: Wang, Yizhi, et al.
Pubblicazione: (2025)

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

What Matters in Transformers? Not All Attention is Needed
di: He, Shwai, et al.
Pubblicazione: (2024)

Common Sense Is All You Need
di: Latapie, Hugo
Pubblicazione: (2025)

Ideal Registration? Segmentation is All You Need
di: Chen, Xiang, et al.
Pubblicazione: (2025)

A Single Goal is All You Need: Skills and Exploration Emerge from Contrastive RL without Rewards, Demonstrations, or Subgoals
di: Liu, Grace, et al.
Pubblicazione: (2024)

Language is All a Graph Needs
di: Ye, Ruosong, et al.
Pubblicazione: (2023)

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

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

Not All Layers Need Tuning: Selective Layer Restoration Recovers Diversity
di: Zhang, Bowen, et al.
Pubblicazione: (2026)

Are Tools All We Need? Unveiling the Tool-Use Tax in LLM Agents
di: Zhang, Kaituo, et al.
Pubblicazione: (2026)

The Residual Stream Is All You Need: On the Redundancy of the KV Cache in Transformer Inference
di: Qasim, Kaleem Ullah, et al.
Pubblicazione: (2026)

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

Context is All You Need
di: Delanois, Jean Erik, et al.
Pubblicazione: (2026)

Information Gain Is Not All You Need
di: Ericson, Ludvig, et al.
Pubblicazione: (2025)

Contrast Is All You Need
di: Kilic, Burak, et al.
Pubblicazione: (2023)

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

Goal-Conditioned Agents that Learn Everything All at Once
di: Matthews, Michael, et al.
Pubblicazione: (2026)

Bridging Efficiency and Transparency: Explainable CoT Compression in Multimodal Large Reasoning Models
di: Wang, Yizhi, et al.
Pubblicazione: (2026)

Attention is All You Need Until You Need Retention
di: Yaslioglu, M. Murat
Pubblicazione: (2025)

Reasoning Is All You Need for Urban Planning AI
di: Yang, Sijie, et al.
Pubblicazione: (2025)

Memory augment is All You Need for image restoration
di: Zhang, Xiao Feng, et al.
Pubblicazione: (2023)

TransMLA: Multi-Head Latent Attention Is All You Need
di: Meng, Fanxu, et al.
Pubblicazione: (2025)

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

Exploitation Is All You Need... for Exploration
di: Rentschler, Micah, et al.
Pubblicazione: (2025)

Were RNNs All We Needed?
di: Feng, Leo, et al.
Pubblicazione: (2024)

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

Avoiding Premature Collapse: Adaptive Annealing for Entropy-Regularized Structural Inference
di: Liu, Yizhi
Pubblicazione: (2026)

The Homogeneity Trap: Spectral Collapse in Doubly-Stochastic Deep Networks
di: Liu, Yizhi
Pubblicazione: (2026)

Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts
di: Gan, Chunjing, et al.
Pubblicazione: (2024)

SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN
di: You, Kang, et al.
Pubblicazione: (2024)

COIG-CQIA: Quality is All You Need for Chinese Instruction Fine-tuning
di: Bai, Yuelin, et al.
Pubblicazione: (2024)

Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM
di: Lu, Xiaoding, et al.
Pubblicazione: (2024)

[MASK] is All You Need
di: Hu, Vincent Tao, et al.
Pubblicazione: (2024)

Self-supervised Dataset Distillation: A Good Compression Is All You Need
di: Zhou, Muxin, et al.
Pubblicazione: (2024)

Towards Goal-oriented Intelligent Tutoring Systems in Online Education
di: Deng, Yang, et al.
Pubblicazione: (2023)

Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4
di: Bsharat, Sondos Mahmoud, et al.
Pubblicazione: (2023)

All You Need Is Synthetic Task Augmentation
di: Godin, Guillaume
Pubblicazione: (2025)

Element-wise Attention Is All You Need
di: Feng, Guoxin
Pubblicazione: (2025)