Cover Image

Cross-Layer Discrete Concept Discovery for Interpreting Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Garg, Ankur, Yu, Xuemin, Sajjad, Hassan, Kahou, Samira Ebrahimi
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Vector Quantized Latent Concepts: A Scalable Alternative to Clustering-Based Concept Discovery
by: Yu, Xuemin, et al.
Published: (2026)

KD-LoRA: A Hybrid Approach to Efficient Fine-Tuning with LoRA and Knowledge Distillation
by: Azimi, Rambod, et al.
Published: (2024)

Interpreting the Effects of Quantization on LLMs
by: Singh, Manpreet, et al.
Published: (2025)

Variational Language Concepts for Interpreting Foundation Language Models
by: Wang, Hengyi, et al.
Published: (2024)

Locally Constrained Representations in Reinforcement Learning
by: Nath, Somjit, et al.
Published: (2022)

Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?
by: Jin, Mingyu, et al.
Published: (2024)

Concept Layers: Enhancing Interpretability and Intervenability via LLM Conceptualization
by: Bidusa, Or Raphael, et al.
Published: (2025)

Neurons Speak in Ranges: Breaking Free from Discrete Neuronal Attribution
by: Haider, Muhammad Umair, et al.
Published: (2025)

Interpreting Language Models Through Concept Descriptions: A Survey
by: Feldhus, Nils, et al.
Published: (2025)

Quantifying the Capabilities of LLMs across Scale and Precision
by: Badshah, Sher, et al.
Published: (2024)

LangFIR: Discovering Sparse Language-Specific Features from Monolingual Data for Language Steering
by: Wong, Sing Hieng, et al.
Published: (2026)

Fairness Under Demographic Scarce Regime
by: Kenfack, Patrik Joslin, et al.
Published: (2023)

From Concepts to Components: Concept-Agnostic Attention Module Discovery in Transformers
by: Su, Jingtong, et al.
Published: (2025)

Layer Swapping for Zero-Shot Cross-Lingual Transfer in Large Language Models
by: Bandarkar, Lucas, et al.
Published: (2024)

A New Method for Cross-Lingual-based Semantic Role Labeling
by: Ebrahimi, Mohammad, et al.
Published: (2024)

Correlated Errors in Large Language Models
by: Kim, Elliot, et al.
Published: (2025)

DiscoveryBench: Towards Data-Driven Discovery with Large Language Models
by: Majumder, Bodhisattwa Prasad, et al.
Published: (2024)

Decoding Dark Matter: Specialized Sparse Autoencoders for Interpreting Rare Concepts in Foundation Models
by: Muhamed, Aashiq, et al.
Published: (2024)

Geometry-Lite: Interpretable Safety Probing via Layer-Wise Margin Geometry
by: Sim, Woo Seob, et al.
Published: (2026)

REQUAL-LM: Reliability and Equity through Aggregation in Large Language Models
by: Ebrahimi, Sana, et al.
Published: (2024)

Layer by Layer: Uncovering Hidden Representations in Language Models
by: Skean, Oscar, et al.
Published: (2025)

Use Sparse Autoencoders to Discover Unknown Concepts, Not to Act on Known Concepts
by: Peng, Kenny, et al.
Published: (2025)

Knowledge Boundary Discovery for Large Language Models
by: Wang, Ziquan, et al.
Published: (2026)

Reinforcement Learning for Sequence Design Leveraging Protein Language Models
by: Subramanian, Jithendaraa, et al.
Published: (2024)

Mitigating Hallucinated Translations in Large Language Models with Hallucination-focused Preference Optimization
by: Tang, Zilu, et al.
Published: (2025)

Non-Markovian Discrete Diffusion with Causal Language Models
by: Zhang, Yangtian, et al.
Published: (2025)

Latent Concept Disentanglement in Transformer-based Language Models
by: Hong, Guan Zhe, et al.
Published: (2025)

The Geometry of Categorical and Hierarchical Concepts in Large Language Models
by: Park, Kiho, et al.
Published: (2024)

Predictive Concept Decoders: Training Scalable End-to-End Interpretability Assistants
by: Huang, Vincent, et al.
Published: (2025)

Learning to Interpret Weight Differences in Language Models
by: Goel, Avichal, et al.
Published: (2025)

Rethinking Interpretability in the Era of Large Language Models
by: Singh, Chandan, et al.
Published: (2024)

DLM-Scope: Mechanistic Interpretability of Diffusion Language Models via Sparse Autoencoders
by: Wang, Xu, et al.
Published: (2026)

Latent Principle Discovery for Language Model Self-Improvement
by: Ramji, Keshav, et al.
Published: (2025)

Generalized Category Discovery with Large Language Models in the Loop
by: An, Wenbin, et al.
Published: (2023)

Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress?
by: Jeong, Daniel P., et al.
Published: (2024)

LayerIF: Estimating Layer Quality for Large Language Models using Influence Functions
by: Askari, Hadi, et al.
Published: (2025)

Improving Large Language Models with Concept-Aware Fine-Tuning
by: Chen, Michael K., et al.
Published: (2025)

Recursive Concept Evolution for Compositional Reasoning in Large Language Models
by: Chaudhry, Sarim
Published: (2026)

Recursive Introspection: Teaching Language Model Agents How to Self-Improve
by: Qu, Yuxiao, et al.
Published: (2024)

Geometric Interpretation of Layer Normalization and a Comparative Analysis with RMSNorm
by: Gupta, Akshat, et al.
Published: (2024)