A is for Absorption: Studying Feature Splitting and Absorption in Sparse Autoencoders
Fuente:
arXiv
Saved in:
| Main Authors: | Chanin, David, Wilken-Smith, James, Dulka, Tomáš, Bhatnagar, Hardik, Golechha, Satvik, Bloom, Joseph |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Feature Hedging: Correlated Features Break Narrow Sparse Autoencoders
by: Chanin, David, et al.
Published: (2025)
by: Chanin, David, et al.
Published: (2025)
Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders
by: Chanin, David, et al.
Published: (2025)
by: Chanin, David, et al.
Published: (2025)
NICE: To Optimize In-Context Examples or Not?
by: Srivastava, Pragya, et al.
Published: (2024)
by: Srivastava, Pragya, et al.
Published: (2024)
Are Sparse Autoencoder Benchmarks Reliable?
by: Chanin, David
Published: (2026)
by: Chanin, David
Published: (2026)
Progress Measures for Grokking on Real-world Tasks
by: Golechha, Satvik
Published: (2024)
by: Golechha, Satvik
Published: (2024)
ABBEL: LLM Agents Acting through Belief Bottlenecks Expressed in Language
by: Lidayan, Aly, et al.
Published: (2025)
by: Lidayan, Aly, et al.
Published: (2025)
Challenges in Mechanistically Interpreting Model Representations
by: Golechha, Satvik, et al.
Published: (2024)
by: Golechha, Satvik, et al.
Published: (2024)
Building Better Deception Probes Using Targeted Instruction Pairs
by: Natarajan, Vikram, et al.
Published: (2026)
by: Natarajan, Vikram, et al.
Published: (2026)
Sparse Autoencoder Features for Classifications and Transferability
by: Gallifant, Jack, et al.
Published: (2025)
by: Gallifant, Jack, et al.
Published: (2025)
Identifying Linear Relational Concepts in Large Language Models
by: Chanin, David, et al.
Published: (2023)
by: Chanin, David, et al.
Published: (2023)
Among Us: A Sandbox for Measuring and Detecting Agentic Deception
by: Golechha, Satvik, et al.
Published: (2025)
by: Golechha, Satvik, et al.
Published: (2025)
Improving Steering Vectors by Targeting Sparse Autoencoder Features
by: Chalnev, Sviatoslav, et al.
Published: (2024)
by: Chalnev, Sviatoslav, et al.
Published: (2024)
SynthSAEBench: Evaluating Sparse Autoencoders on Scalable Realistic Synthetic Data
by: Chanin, David, et al.
Published: (2026)
by: Chanin, David, et al.
Published: (2026)
SparseRM: A Lightweight Preference Modeling with Sparse Autoencoder
by: Liu, Dengcan, et al.
Published: (2025)
by: Liu, Dengcan, et al.
Published: (2025)
Constrain Alignment with Sparse Autoencoders
by: Yin, Qingyu, et al.
Published: (2024)
by: Yin, Qingyu, et al.
Published: (2024)
AbsTopK: Rethinking Sparse Autoencoders For Bidirectional Features
by: Zhu, Xudong, et al.
Published: (2025)
by: Zhu, Xudong, et al.
Published: (2025)
Mechanistic Knobs in LLMs: Retrieving and Steering High-Order Semantic Features via Sparse Autoencoders
by: Zhang, Ruikang, et al.
Published: (2026)
by: Zhang, Ruikang, et al.
Published: (2026)
Quantifying Feature Space Universality Across Large Language Models via Sparse Autoencoders
by: Lan, Michael, et al.
Published: (2024)
by: Lan, Michael, et al.
Published: (2024)
Sparse Autoencoders for Hypothesis Generation
by: Movva, Rajiv, et al.
Published: (2025)
by: Movva, Rajiv, et al.
Published: (2025)
How Do LLMs Encode Scientific Quality? An Empirical Study Using Monosemantic Features from Sparse Autoencoders
by: McCoubrey, Michael, et al.
Published: (2026)
by: McCoubrey, Michael, et al.
Published: (2026)
Training Neural Networks for Modularity aids Interpretability
by: Golechha, Satvik, et al.
Published: (2024)
by: Golechha, Satvik, et al.
Published: (2024)
SAFER: Probing Safety in Reward Models with Sparse Autoencoder
by: Shi, Wei, et al.
Published: (2025)
by: Shi, Wei, et al.
Published: (2025)
Toward Faithful Retrieval-Augmented Generation with Sparse Autoencoders
by: Xiong, Guangzhi, et al.
Published: (2025)
by: Xiong, Guangzhi, et al.
Published: (2025)
Time-Aware Feature Selection: Adaptive Temporal Masking for Stable Sparse Autoencoder Training
by: Li, T. Ed, et al.
Published: (2025)
by: Li, T. Ed, et al.
Published: (2025)
Decoding Dark Matter: Specialized Sparse Autoencoders for Interpreting Rare Concepts in Foundation Models
by: Muhamed, Aashiq, et al.
Published: (2024)
by: Muhamed, Aashiq, et al.
Published: (2024)
Controllable LLM Reasoning via Sparse Autoencoder-Based Steering
by: Fang, Yi, et al.
Published: (2026)
by: Fang, Yi, et al.
Published: (2026)
Disentangling concept semantics via multilingual averaging in Sparse Autoencoders
by: O'Reilly, Cliff, et al.
Published: (2025)
by: O'Reilly, Cliff, et al.
Published: (2025)
Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders
by: Xuan, Richmond Sin Jing, et al.
Published: (2025)
by: Xuan, Richmond Sin Jing, et al.
Published: (2025)
Dissecting Chronos: Sparse Autoencoders Reveal Causal Feature Hierarchies in Time Series Foundation Models
by: Mishra, Anurag
Published: (2026)
by: Mishra, Anurag
Published: (2026)
FaithfulSAE: Towards Capturing Faithful Features with Sparse Autoencoders without External Dataset Dependencies
by: Cho, Seonglae, et al.
Published: (2025)
by: Cho, Seonglae, et al.
Published: (2025)
Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering
by: Zhao, Haiyan, et al.
Published: (2025)
by: Zhao, Haiyan, et al.
Published: (2025)
Layer-Wise Perturbations via Sparse Autoencoders for Adversarial Text Generation
by: Shu, Huizhen, et al.
Published: (2025)
by: Shu, Huizhen, et al.
Published: (2025)
Sparse Autoencoder Decomposition of Clinical Sequence Model Representations: Feature Complexity, Task Specialisation, and Mortality Prediction
by: Sainsbury, Chris, et al.
Published: (2026)
by: Sainsbury, Chris, et al.
Published: (2026)
Enabling Precise Topic Alignment in Large Language Models Via Sparse Autoencoders
by: Joshi, Ananya, et al.
Published: (2025)
by: Joshi, Ananya, et al.
Published: (2025)
Incorporating Hierarchical Semantics in Sparse Autoencoder Architectures
by: Muchane, Mark, et al.
Published: (2025)
by: Muchane, Mark, et al.
Published: (2025)
Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2
by: Lieberum, Tom, et al.
Published: (2024)
by: Lieberum, Tom, et al.
Published: (2024)
SMoA: Improving Multi-agent Large Language Models with Sparse Mixture-of-Agents
by: Li, Dawei, et al.
Published: (2024)
by: Li, Dawei, et al.
Published: (2024)
Lost in Translation? A Comparative Study on the Cross-Lingual Transfer of Composite Harms
by: Shukla, Vaibhav, et al.
Published: (2026)
by: Shukla, Vaibhav, et al.
Published: (2026)
Jacobian Sparse Autoencoders: Sparsify Computations, Not Just Activations
by: Farnik, Lucy, et al.
Published: (2025)
by: Farnik, Lucy, et al.
Published: (2025)
Evaluating Adversarial Robustness of Concept Representations in Sparse Autoencoders
by: Li, Aaron J., et al.
Published: (2025)
by: Li, Aaron J., et al.
Published: (2025)
Similar Items
-
Feature Hedging: Correlated Features Break Narrow Sparse Autoencoders
by: Chanin, David, et al.
Published: (2025) -
Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders
by: Chanin, David, et al.
Published: (2025) -
NICE: To Optimize In-Context Examples or Not?
by: Srivastava, Pragya, et al.
Published: (2024) -
Are Sparse Autoencoder Benchmarks Reliable?
by: Chanin, David
Published: (2026) -
Progress Measures for Grokking on Real-world Tasks
by: Golechha, Satvik
Published: (2024)