Saved in:
| Main Authors: | Liu, Sannyuya, Li, Qing, Shen, Xiaoxuan, Sun, Jianwen, Yang, Zongkai |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2404.05689 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
COMET: "Cone of experience" enhanced large multimodal model for mathematical problem generation
by: Liu, Sannyuya, et al.
Published: (2024)
by: Liu, Sannyuya, et al.
Published: (2024)
Beyond Error-Based Optimization: Experience-Driven Symbolic Regression with Goal-Conditioned Reinforcement Learning
by: Sun, Jianwen, et al.
Published: (2026)
by: Sun, Jianwen, et al.
Published: (2026)
Mitigating Overthinking in Large Reasoning Models via Difficulty-aware Reinforcement Learning
by: Wan, Qian, et al.
Published: (2026)
by: Wan, Qian, et al.
Published: (2026)
Discovering physical laws with parallel symbolic enumeration
by: Ruan, Kai, et al.
Published: (2024)
by: Ruan, Kai, et al.
Published: (2024)
Sloth: scaling laws for LLM skills to predict multi-benchmark performance across families
by: Polo, Felipe Maia, et al.
Published: (2024)
by: Polo, Felipe Maia, et al.
Published: (2024)
Using reinforcement learning to probe the role of feedback in skill acquisition
by: Terpin, Antonio, et al.
Published: (2025)
by: Terpin, Antonio, et al.
Published: (2025)
An Offline Adaptation Framework for Constrained Multi-Objective Reinforcement Learning
by: Lin, Qian, et al.
Published: (2024)
by: Lin, Qian, et al.
Published: (2024)
Policy-regularized Offline Multi-objective Reinforcement Learning
by: Lin, Qian, et al.
Published: (2024)
by: Lin, Qian, et al.
Published: (2024)
Bound by semanticity: universal laws governing the generalization-identification tradeoff
by: Nurisso, Marco, et al.
Published: (2025)
by: Nurisso, Marco, et al.
Published: (2025)
LLMs learn governing principles of dynamical systems, revealing an in-context neural scaling law
by: Liu, Toni J. B., et al.
Published: (2024)
by: Liu, Toni J. B., et al.
Published: (2024)
Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization
by: Liu, Zongkai, et al.
Published: (2024)
by: Liu, Zongkai, et al.
Published: (2024)
FLEKE: Federated Locate-then-Edit Knowledge Editing
by: Zhao, Zongkai, et al.
Published: (2025)
by: Zhao, Zongkai, et al.
Published: (2025)
Neuro-symbolic Learning Yielding Logical Constraints
by: Li, Zenan, et al.
Published: (2024)
by: Li, Zenan, et al.
Published: (2024)
CPGD: Toward Stable Rule-based Reinforcement Learning for Language Models
by: Liu, Zongkai, et al.
Published: (2025)
by: Liu, Zongkai, et al.
Published: (2025)
Softened Symbol Grounding for Neuro-symbolic Systems
by: Li, Zenan, et al.
Published: (2024)
by: Li, Zenan, et al.
Published: (2024)
Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation
by: Zhou, Zhijian, et al.
Published: (2025)
by: Zhou, Zhijian, et al.
Published: (2025)
Fixed Random Classifier Rearrangement for Continual Learning
by: Huang, Shengyang, et al.
Published: (2024)
by: Huang, Shengyang, et al.
Published: (2024)
Curiosity-driven RL for symbolic equation solving
by: O'Keeffe, Kevin P.
Published: (2025)
by: O'Keeffe, Kevin P.
Published: (2025)
Neuro-symbolic Weak Supervision: Theory and Semantics
by: Upreti, Nijesh, et al.
Published: (2025)
by: Upreti, Nijesh, et al.
Published: (2025)
Gradual Vigilance and Interval Communication: Enhancing Value Alignment in Multi-Agent Debates
by: Zou, Rui, et al.
Published: (2024)
by: Zou, Rui, et al.
Published: (2024)
Regularized Multi-LLMs Collaboration for Enhanced Score-based Causal Discovery
by: Li, Xiaoxuan, et al.
Published: (2024)
by: Li, Xiaoxuan, et al.
Published: (2024)
Discrete, compositional, and symbolic representations through attractor dynamics
by: Nam, Andrew, et al.
Published: (2023)
by: Nam, Andrew, et al.
Published: (2023)
Neuro-symbolic Action Masking for Deep Reinforcement Learning
by: Han, Shuai, et al.
Published: (2026)
by: Han, Shuai, et al.
Published: (2026)
Learning neuro-symbolic convergent term rewriting systems
by: Petruzzellis, Flavio, et al.
Published: (2025)
by: Petruzzellis, Flavio, et al.
Published: (2025)
To Compress or Not? Pushing the Frontier of Lossless GenAI Model Weights Compression with Exponent Concentration
by: Yang, Zeyu, et al.
Published: (2025)
by: Yang, Zeyu, et al.
Published: (2025)
Scaling laws for learning with real and surrogate data
by: Jain, Ayush, et al.
Published: (2024)
by: Jain, Ayush, et al.
Published: (2024)
HTG-GCL: Leveraging Hierarchical Topological Granularity from Cellular Complexes for Graph Contrastive Learning
by: Ji, Qirui, et al.
Published: (2025)
by: Ji, Qirui, et al.
Published: (2025)
LLM-ABBA: Understanding time series via symbolic approximation
by: Chen, Xinye, et al.
Published: (2024)
by: Chen, Xinye, et al.
Published: (2024)
Quantifying Sensitivity for Tree Ensembles: A symbolic and compositional approach
by: Akshay, S., et al.
Published: (2026)
by: Akshay, S., et al.
Published: (2026)
The Role of Deductive and Inductive Reasoning in Large Language Models
by: Cai, Chengkun, et al.
Published: (2024)
by: Cai, Chengkun, et al.
Published: (2024)
Combinatorial Optimization with Automated Graph Neural Networks
by: Liu, Yang, et al.
Published: (2024)
by: Liu, Yang, et al.
Published: (2024)
Evaluating the Design Features of an Intelligent Tutoring System for Advanced Mathematics Learning
by: Fang, Ying, et al.
Published: (2024)
by: Fang, Ying, et al.
Published: (2024)
Deconfounded Causality-aware Parameter-Efficient Fine-Tuning for Problem-Solving Improvement of LLMs
by: Wang, Ruoyu, et al.
Published: (2024)
by: Wang, Ruoyu, et al.
Published: (2024)
Explainable Moral Values: a neuro-symbolic approach to value classification
by: Lazzari, Nicolas, et al.
Published: (2024)
by: Lazzari, Nicolas, et al.
Published: (2024)
On the origin of neural scaling laws: from random graphs to natural language
by: Barkeshli, Maissam, et al.
Published: (2026)
by: Barkeshli, Maissam, et al.
Published: (2026)
Auxiliary task discovery through generate-and-test
by: Rafiee, Banafsheh, et al.
Published: (2022)
by: Rafiee, Banafsheh, et al.
Published: (2022)
Time series causal discovery with variable lags
by: Petrungaro, Bruno, et al.
Published: (2026)
by: Petrungaro, Bruno, et al.
Published: (2026)
Benchmarking symbolic regression constant optimization schemes
by: Reis, L. G. A dos, et al.
Published: (2024)
by: Reis, L. G. A dos, et al.
Published: (2024)
When can transformers reason with abstract symbols?
by: Boix-Adsera, Enric, et al.
Published: (2023)
by: Boix-Adsera, Enric, et al.
Published: (2023)
Learning Neuro-symbolic Programs for Language Guided Robot Manipulation
by: Kalithasan, Namasivayam, et al.
Published: (2022)
by: Kalithasan, Namasivayam, et al.
Published: (2022)
Similar Items
-
COMET: "Cone of experience" enhanced large multimodal model for mathematical problem generation
by: Liu, Sannyuya, et al.
Published: (2024) -
Beyond Error-Based Optimization: Experience-Driven Symbolic Regression with Goal-Conditioned Reinforcement Learning
by: Sun, Jianwen, et al.
Published: (2026) -
Mitigating Overthinking in Large Reasoning Models via Difficulty-aware Reinforcement Learning
by: Wan, Qian, et al.
Published: (2026) -
Discovering physical laws with parallel symbolic enumeration
by: Ruan, Kai, et al.
Published: (2024) -
Sloth: scaling laws for LLM skills to predict multi-benchmark performance across families
by: Polo, Felipe Maia, et al.
Published: (2024)