EmbedLLM: Learning Compact Representations of Large Language Models
Fuente:
arXiv
Saved in:
| Main Authors: | Zhuang, Richard, Wu, Tianhao, Wen, Zhaojin, Li, Andrew, Jiao, Jiantao, Ramchandran, Kannan |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Sample Complexity and Representation Ability of Test-time Scaling Paradigms
by: Huang, Baihe, et al.
Published: (2025)
by: Huang, Baihe, et al.
Published: (2025)
Toward a Theory of Tokenization in LLMs
by: Rajaraman, Nived, et al.
Published: (2024)
by: Rajaraman, Nived, et al.
Published: (2024)
Towards Anytime-Valid Statistical Watermarking
by: Huang, Baihe, et al.
Published: (2026)
by: Huang, Baihe, et al.
Published: (2026)
ProxySPEX: Inference-Efficient Interpretability via Sparse Feature Interactions in LLMs
by: Butler, Landon, et al.
Published: (2025)
by: Butler, Landon, et al.
Published: (2025)
Understanding Survey Paper Taxonomy about Large Language Models via Graph Representation Learning
by: Zhuang, Jun, et al.
Published: (2024)
by: Zhuang, Jun, et al.
Published: (2024)
A Timeline and Analysis for Representation Plasticity in Large Language Models
by: Kannan, Akshat
Published: (2024)
by: Kannan, Akshat
Published: (2024)
Quantifying Positional Biases in Text Embedding Models
by: Lee, Reagan J., et al.
Published: (2024)
by: Lee, Reagan J., et al.
Published: (2024)
$\text{M}^{2}$LLM: Multi-view Molecular Representation Learning with Large Language Models
by: Ju, Jiaxin, et al.
Published: (2025)
by: Ju, Jiaxin, et al.
Published: (2025)
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
by: Zhu, Banghua, et al.
Published: (2024)
by: Zhu, Banghua, et al.
Published: (2024)
When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?
by: Gao, Yanjun, et al.
Published: (2024)
by: Gao, Yanjun, et al.
Published: (2024)
Improving Large Language Model Safety with Contrastive Representation Learning
by: Simko, Samuel, et al.
Published: (2025)
by: Simko, Samuel, et al.
Published: (2025)
LLMs as Zero-shot Graph Learners: Alignment of GNN Representations with LLM Token Embeddings
by: Wang, Duo, et al.
Published: (2024)
by: Wang, Duo, et al.
Published: (2024)
$\texttt{SPECS}$: Faster Test-Time Scaling through Speculative Drafts
by: Cemri, Mert, et al.
Published: (2025)
by: Cemri, Mert, et al.
Published: (2025)
Uncovering Emergent Physics Representations Learned In-Context by Large Language Models
by: Song, Yeongwoo, et al.
Published: (2025)
by: Song, Yeongwoo, et al.
Published: (2025)
A Positive Case for Faithfulness: LLM Self-Explanations Help Predict Model Behavior
by: Mayne, Harry, et al.
Published: (2026)
by: Mayne, Harry, et al.
Published: (2026)
Demystifying Embedding Spaces using Large Language Models
by: Tennenholtz, Guy, et al.
Published: (2023)
by: Tennenholtz, Guy, et al.
Published: (2023)
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)
zrLLM: Zero-Shot Relational Learning on Temporal Knowledge Graphs with Large Language Models
by: Ding, Zifeng, et al.
Published: (2023)
by: Ding, Zifeng, et al.
Published: (2023)
LLM-NEO: Parameter Efficient Knowledge Distillation for Large Language Models
by: Yang, Runming, et al.
Published: (2024)
by: Yang, Runming, et al.
Published: (2024)
RouteLLM: Learning to Route LLMs with Preference Data
by: Ong, Isaac, et al.
Published: (2024)
by: Ong, Isaac, et al.
Published: (2024)
Large Language Model Unlearning via Embedding-Corrupted Prompts
by: Liu, Chris Yuhao, et al.
Published: (2024)
by: Liu, Chris Yuhao, et al.
Published: (2024)
SelfIE: Self-Interpretation of Large Language Model Embeddings
by: Chen, Haozhe, et al.
Published: (2024)
by: Chen, Haozhe, et al.
Published: (2024)
Rhetorical Questions in LLM Representations: A Linear Probing Study
by: Yao, Louie Hong, et al.
Published: (2026)
by: Yao, Louie Hong, et al.
Published: (2026)
Advancing Graph Representation Learning with Large Language Models: A Comprehensive Survey of Techniques
by: Mao, Qiheng, et al.
Published: (2024)
by: Mao, Qiheng, et al.
Published: (2024)
GPT and Prejudice: A Sparse Approach to Understanding Learned Representations in Large Language Models
by: Mahran, Mariam, et al.
Published: (2025)
by: Mahran, Mariam, et al.
Published: (2025)
Test-Time Learning for Large Language Models
by: Hu, Jinwu, et al.
Published: (2025)
by: Hu, Jinwu, et al.
Published: (2025)
User-LLM: Efficient LLM Contextualization with User Embeddings
by: Ning, Lin, et al.
Published: (2024)
by: Ning, Lin, et al.
Published: (2024)
The Linear Representation Hypothesis and the Geometry of Large Language Models
by: Park, Kiho, et al.
Published: (2023)
by: Park, Kiho, et al.
Published: (2023)
EfficientLLM: Efficiency in Large Language Models
by: Yuan, Zhengqing, et al.
Published: (2025)
by: Yuan, Zhengqing, et al.
Published: (2025)
Improving Uncertainty Quantification in Large Language Models via Semantic Embeddings
by: Grewal, Yashvir S., et al.
Published: (2024)
by: Grewal, Yashvir S., et al.
Published: (2024)
SPEX: Scaling Feature Interaction Explanations for LLMs
by: Kang, Justin Singh, et al.
Published: (2025)
by: Kang, Justin Singh, et al.
Published: (2025)
A Simple and Effective Pruning Approach for Large Language Models
by: Sun, Mingjie, et al.
Published: (2023)
by: Sun, Mingjie, et al.
Published: (2023)
A Survey of Quantized Graph Representation Learning: Connecting Graph Structures with Large Language Models
by: Lin, Qika, et al.
Published: (2025)
by: Lin, Qika, et al.
Published: (2025)
FLUID-LLM: Learning Computational Fluid Dynamics with Spatiotemporal-aware Large Language Models
by: Zhu, Max, et al.
Published: (2024)
by: Zhu, Max, et al.
Published: (2024)
Can Large Language Models Understand Intermediate Representations in Compilers?
by: Jiang, Hailong, et al.
Published: (2025)
by: Jiang, Hailong, et al.
Published: (2025)
Analyzing the Role of Semantic Representations in the Era of Large Language Models
by: Jin, Zhijing, et al.
Published: (2024)
by: Jin, Zhijing, et al.
Published: (2024)
Representational Curvature Modulates Behavioral Uncertainty in Large Language Models
by: King, Jack, et al.
Published: (2026)
by: King, Jack, et al.
Published: (2026)
Large Language Models Struggle in Token-Level Clinical Named Entity Recognition
by: Lu, Qiuhao, et al.
Published: (2024)
by: Lu, Qiuhao, et al.
Published: (2024)
LLM-Select: Feature Selection with Large Language Models
by: Jeong, Daniel P., et al.
Published: (2024)
by: Jeong, Daniel P., et al.
Published: (2024)
LLM4Delay: Flight Delay Prediction via Cross-Modality Adaptation of Large Language Models and Aircraft Trajectory Representation
by: Phisannupawong, Thaweerath, et al.
Published: (2025)
by: Phisannupawong, Thaweerath, et al.
Published: (2025)
Similar Items
-
Sample Complexity and Representation Ability of Test-time Scaling Paradigms
by: Huang, Baihe, et al.
Published: (2025) -
Toward a Theory of Tokenization in LLMs
by: Rajaraman, Nived, et al.
Published: (2024) -
Towards Anytime-Valid Statistical Watermarking
by: Huang, Baihe, et al.
Published: (2026) -
ProxySPEX: Inference-Efficient Interpretability via Sparse Feature Interactions in LLMs
by: Butler, Landon, et al.
Published: (2025) -
Understanding Survey Paper Taxonomy about Large Language Models via Graph Representation Learning
by: Zhuang, Jun, et al.
Published: (2024)