Saved in:
| Main Author: | Zhang, Yihao |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.20161 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning to Reason as Action Abstractions with Scalable Mid-Training RL
by: Zhang, Shenao, et al.
Published: (2025)
by: Zhang, Shenao, et al.
Published: (2025)
How Causal Abstraction Underpins Computational Explanation
by: Geiger, Atticus, et al.
Published: (2025)
by: Geiger, Atticus, et al.
Published: (2025)
Interpreting Language Models Through Concept Descriptions: A Survey
by: Feldhus, Nils, et al.
Published: (2025)
by: Feldhus, Nils, et al.
Published: (2025)
Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models
by: Marks, Samuel, et al.
Published: (2024)
by: Marks, Samuel, et al.
Published: (2024)
A Survey on Sparse Autoencoders: Interpreting the Internal Mechanisms of Large Language Models
by: Shu, Dong, et al.
Published: (2025)
by: Shu, Dong, et al.
Published: (2025)
Capturing Sparks of Abstraction for the ARC Challenge
by: Andrews, Martin
Published: (2024)
by: Andrews, Martin
Published: (2024)
STELLA: Guiding Large Language Models for Time Series Forecasting with Semantic Abstractions
by: Fan, Junjie, et al.
Published: (2025)
by: Fan, Junjie, et al.
Published: (2025)
Multiple Abstraction Level Retrieve Augment Generation
by: Zheng, Zheng, et al.
Published: (2025)
by: Zheng, Zheng, et al.
Published: (2025)
Small Vision-Language Models: A Survey on Compact Architectures and Techniques
by: Patnaik, Nitesh, et al.
Published: (2025)
by: Patnaik, Nitesh, et al.
Published: (2025)
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models
by: Zheng, Huaixiu Steven, et al.
Published: (2023)
by: Zheng, Huaixiu Steven, et al.
Published: (2023)
Probing the Limits of Compressive Memory: A Study of Infini-Attention in Small-Scale Pretraining
by: Huang, Ruizhe, et al.
Published: (2025)
by: Huang, Ruizhe, et al.
Published: (2025)
A Survey of Reinforcement Learning for Large Reasoning Models
by: Zhang, Kaiyan, et al.
Published: (2025)
by: Zhang, Kaiyan, et al.
Published: (2025)
RLAD: Training LLMs to Discover Abstractions for Solving Reasoning Problems
by: Qu, Yuxiao, et al.
Published: (2025)
by: Qu, Yuxiao, et al.
Published: (2025)
Parallel LLM Reasoning for Bias-Resilient, Robust Conceptual Abstraction
by: Adeseye, Aisvarya, et al.
Published: (2026)
by: Adeseye, Aisvarya, et al.
Published: (2026)
Zamba: A Compact 7B SSM Hybrid Model
by: Glorioso, Paolo, et al.
Published: (2024)
by: Glorioso, Paolo, et al.
Published: (2024)
Causality for Large Language Models
by: Wu, Anpeng, et al.
Published: (2024)
by: Wu, Anpeng, et al.
Published: (2024)
Predicting Compact Phrasal Rewrites with Large Language Models for ASR Post Editing
by: Zhang, Hao, et al.
Published: (2025)
by: Zhang, Hao, et al.
Published: (2025)
When Thinking LLMs Lie: Unveiling the Strategic Deception in Representations of Reasoning Models
by: Wang, Kai, et al.
Published: (2025)
by: Wang, Kai, et al.
Published: (2025)
Causal Inference for Human-Language Model Collaboration
by: Zhang, Bohan, et al.
Published: (2024)
by: Zhang, Bohan, et al.
Published: (2024)
CausalARC: Abstract Reasoning with Causal World Models
by: Maasch, Jacqueline, et al.
Published: (2025)
by: Maasch, Jacqueline, et al.
Published: (2025)
Executable Functional Abstractions: Inferring Generative Programs for Advanced Math Problems
by: Khan, Zaid, et al.
Published: (2025)
by: Khan, Zaid, et al.
Published: (2025)
Distilling LLMs' Decomposition Abilities into Compact Language Models
by: Tarasov, Denis, et al.
Published: (2024)
by: Tarasov, Denis, et al.
Published: (2024)
Compact Language Models via Pruning and Knowledge Distillation
by: Muralidharan, Saurav, et al.
Published: (2024)
by: Muralidharan, Saurav, et al.
Published: (2024)
Non-Markovian Discrete Diffusion with Causal Language Models
by: Zhang, Yangtian, et al.
Published: (2025)
by: Zhang, Yangtian, et al.
Published: (2025)
Instruction Tuning for Large Language Models: A Survey
by: Zhang, Shengyu, et al.
Published: (2023)
by: Zhang, Shengyu, et al.
Published: (2023)
Abstraction Alignment: Comparing Model-Learned and Human-Encoded Conceptual Relationships
by: Boggust, Angie, et al.
Published: (2024)
by: Boggust, Angie, et al.
Published: (2024)
Causal Evaluation of Language Models
by: Chen, Sirui, et al.
Published: (2024)
by: Chen, Sirui, et al.
Published: (2024)
EmbedLLM: Learning Compact Representations of Large Language Models
by: Zhuang, Richard, et al.
Published: (2024)
by: Zhuang, Richard, et al.
Published: (2024)
Variational Language Concepts for Interpreting Foundation Language Models
by: Wang, Hengyi, et al.
Published: (2024)
by: Wang, Hengyi, et al.
Published: (2024)
Large Language Models for Time Series: A Survey
by: Zhang, Xiyuan, et al.
Published: (2024)
by: Zhang, Xiyuan, et al.
Published: (2024)
CausalVLBench: Benchmarking Visual Causal Reasoning in Large Vision-Language Models
by: Komanduri, Aneesh, et al.
Published: (2025)
by: Komanduri, Aneesh, et al.
Published: (2025)
TeleTables: A Benchmark for Large Language Models in Telecom Table Interpretation
by: Ezzakri, Anas, et al.
Published: (2025)
by: Ezzakri, Anas, et al.
Published: (2025)
Reward Models Identify Consistency, Not Causality
by: Xu, Yuhui, et al.
Published: (2025)
by: Xu, Yuhui, et al.
Published: (2025)
CausalRM: Causal-Theoretic Reward Modeling for RLHF from Observational User Feedbacks
by: Wang, Hao, et al.
Published: (2026)
by: Wang, Hao, et al.
Published: (2026)
LLM4Causal: Democratized Causal Tools for Everyone via Large Language Model
by: Jiang, Haitao, et al.
Published: (2023)
by: Jiang, Haitao, et al.
Published: (2023)
Prompting Fairness: Integrating Causality to Debias Large Language Models
by: Li, Jingling, et al.
Published: (2024)
by: Li, Jingling, et al.
Published: (2024)
When Should LLMs Be Less Specific? Selective Abstraction for Reliable Long-Form Text Generation
by: Goren, Shani, et al.
Published: (2026)
by: Goren, Shani, et al.
Published: (2026)
A Meta-Learning Perspective on Transformers for Causal Language Modeling
by: Wu, Xinbo, et al.
Published: (2023)
by: Wu, Xinbo, et al.
Published: (2023)
A Survey on Diffusion Language Models
by: Li, Tianyi, et al.
Published: (2025)
by: Li, Tianyi, et al.
Published: (2025)
Automata Extraction from Transformers
by: Zhang, Yihao, et al.
Published: (2024)
by: Zhang, Yihao, et al.
Published: (2024)
Similar Items
-
Learning to Reason as Action Abstractions with Scalable Mid-Training RL
by: Zhang, Shenao, et al.
Published: (2025) -
How Causal Abstraction Underpins Computational Explanation
by: Geiger, Atticus, et al.
Published: (2025) -
Interpreting Language Models Through Concept Descriptions: A Survey
by: Feldhus, Nils, et al.
Published: (2025) -
Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models
by: Marks, Samuel, et al.
Published: (2024) -
A Survey on Sparse Autoencoders: Interpreting the Internal Mechanisms of Large Language Models
by: Shu, Dong, et al.
Published: (2025)