:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Chen, Ziyu, Xiao, Zhiqing, Jiang, Xinbei, Zhao, Junbo
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2411.15891
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Navigate the Unknown: Enhancing LLM Reasoning with Intrinsic Motivation Guided Exploration
by: Gao, Jingtong, et al.
Published: (2025)

Optimizing Decoding Paths in Masked Diffusion Models by Quantifying Uncertainty
by: Chen, Ziyu, et al.
Published: (2025)

SPA++: Generalized Graph Spectral Alignment for Versatile Domain Adaptation
by: Xiao, Zhiqing, et al.
Published: (2025)

Learning Off-policy with Model-based Intrinsic Motivation For Active Online Exploration
by: Wang, Yibo, et al.
Published: (2024)

Test-Time Training Scaling Laws for Chemical Exploration in Drug Design
by: Thomas, Morgan, et al.
Published: (2025)

Power Law Guided Dynamic Sifting for Efficient Attention
by: Koley, Nirav, et al.
Published: (2025)

Potential-Based Reward Shaping For Intrinsic Motivation
by: Forbes, Grant C., et al.
Published: (2024)

Scaling Laws are Redundancy Laws
by: Bi, Yuda, et al.
Published: (2025)

Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms
by: Rafailov, Rafael, et al.
Published: (2024)

Semantic-Space Exploration and Exploitation in RLVR for LLM Reasoning
by: Huang, Fanding, et al.
Published: (2025)

From Data to Laws: Neural Discovery of Conservation Laws Without False Positives
by: Ray, Rahul D
Published: (2026)

Simulation-Free Differential Dynamics through Neural Conservation Laws
by: Hua, Mengjian, et al.
Published: (2025)

A Hitchhiker's Guide to Scaling Law Estimation
by: Choshen, Leshem, et al.
Published: (2024)

Beyond Scaling Law: A Data-Efficient Distillation Framework for Reasoning
by: Wu, Xiaojun, et al.
Published: (2025)

Towards Neural Scaling Laws on Graphs
by: Liu, Jingzhe, et al.
Published: (2024)

Towards Scaling Law Analysis For Spatiotemporal Weather Data
by: Kiefer, Alexander, et al.
Published: (2026)

From Zipf's Law to Neural Scaling through Heaps' Law and Hilberg's Hypothesis
by: Dębowski, Łukasz
Published: (2025)

Power-Law Spectrum of the Random Feature Model
by: Paquette, Elliot, et al.
Published: (2026)

Breaking the Reward Barrier: Accelerating Tree-of-Thought Reasoning via Speculative Exploration
by: Zhong, Shuzhang, et al.
Published: (2026)

Predictive Scaling Laws for Efficient GRPO Training of Large Reasoning Models
by: Nimmaturi, Datta, et al.
Published: (2025)

On Neural Scaling Laws for Weather Emulation through Continual Training
by: Subramanian, Shashank, et al.
Published: (2026)

LawLLM: Law Large Language Model for the US Legal System
by: Shu, Dong, et al.
Published: (2024)

An Invariant Latent Space Perspective on Language Model Inversion
by: Ye, Wentao, et al.
Published: (2025)

Breaking Neural Network Scaling Laws with Modularity
by: Boopathy, Akhilan, et al.
Published: (2024)

Improved Bounds for Reward-Agnostic and Reward-Free Exploration
by: Ridel, Oran, et al.
Published: (2026)

Preference-Guided Reinforcement Learning for Efficient Exploration
by: Wang, Guojian, et al.
Published: (2024)

The Power of Power Law: Asymmetry Enables Compositional Reasoning
by: Wang, Zixuan, et al.
Published: (2026)

Scaling Laws For Mixed Quantization
by: Cao, Zeyu, et al.
Published: (2024)

Exploration vs Exploitation: Rethinking RLVR through Clipping, Entropy, and Spurious Reward
by: Chen, Peter, et al.
Published: (2025)

P$^2$ Law: Scaling Law for Post-Training After Model Pruning
by: Chen, Xiaodong, et al.
Published: (2024)

Abide by the Law and Follow the Flow: Conservation Laws for Gradient Flows
by: Marcotte, Sibylle, et al.
Published: (2023)

LLM Reasoning with Process Rewards for Outcome-Guided Steps
by: Rezaei, Mohammad, et al.
Published: (2026)

Entropy-Guided Data-Efficient Training for Multimodal Reasoning Reward Models
by: Yang, Shidong, et al.
Published: (2026)

Adaptive Milestone Reward for GUI Agents
by: Zheng, Congmin, et al.
Published: (2026)

Generative Auto-Bidding with Value-Guided Explorations
by: Gao, Jingtong, et al.
Published: (2025)

Analyzing Neural Scaling Laws in Two-Layer Networks with Power-Law Data Spectra
by: Worschech, Roman, et al.
Published: (2024)

Active Budget Allocation for Efficient Scaling Law Estimation via Surrogate-Guided Pruning
by: Schram, Viktoria, et al.
Published: (2026)

Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws
by: Jiang, Yiding, et al.
Published: (2024)

From One-Pass SGD to Data Reuse: Mini-Batch Scaling Laws in Sketched Linear Regression
by: Chen, Ziyan, et al.
Published: (2026)

KMLP: A Scalable Hybrid Architecture for Web-Scale Tabular Data Modeling
by: Zhang, Mingming, et al.
Published: (2026)