Understanding LLM Embeddings for Regression
Fuente:
arXiv
Saved in:
| Main Authors: | Tang, Eric, Yang, Bangding, Song, Xingyou |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Decoding-based Regression
by: Song, Xingyou, et al.
Published: (2025)
by: Song, Xingyou, et al.
Published: (2025)
OmniPred: Language Models as Universal Regressors
by: Song, Xingyou, et al.
Published: (2024)
by: Song, Xingyou, et al.
Published: (2024)
Regression Language Models for Code
by: Akhauri, Yash, et al.
Published: (2025)
by: Akhauri, Yash, et al.
Published: (2025)
Language Model Embeddings Can Be Sufficient for Bayesian Optimization
by: Nguyen, Tung, et al.
Published: (2024)
by: Nguyen, Tung, et al.
Published: (2024)
Understanding the Effects of RLHF on LLM Generalisation and Diversity
by: Kirk, Robert, et al.
Published: (2023)
by: Kirk, Robert, et al.
Published: (2023)
Understanding the planning of LLM agents: A survey
by: Huang, Xu, et al.
Published: (2024)
by: Huang, Xu, et al.
Published: (2024)
One Swallow Does Not Make a Summer: Understanding Semantic Structures in Embedding Spaces
by: Sun, Yandong, et al.
Published: (2025)
by: Sun, Yandong, 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)
Understanding Token Probability Encoding in Output Embeddings
by: Cho, Hakaze, et al.
Published: (2024)
by: Cho, Hakaze, et al.
Published: (2024)
Understanding Emergent In-Context Learning from a Kernel Regression Perspective
by: Han, Chi, et al.
Published: (2023)
by: Han, Chi, et al.
Published: (2023)
Aligned at the Start: Conceptual Groupings in LLM Embeddings
by: Khatir, Mehrdad, et al.
Published: (2024)
by: Khatir, Mehrdad, et al.
Published: (2024)
Output Embedding Centering for Stable LLM Pretraining
by: Stollenwerk, Felix, et al.
Published: (2026)
by: Stollenwerk, Felix, et al.
Published: (2026)
Latent Space Chain-of-Embedding Enables Output-free LLM Self-Evaluation
by: Wang, Yiming, et al.
Published: (2024)
by: Wang, Yiming, et al.
Published: (2024)
LLM-as-a-Prophet: Understanding Predictive Intelligence with Prophet Arena
by: Yang, Qingchuan, et al.
Published: (2025)
by: Yang, Qingchuan, et al.
Published: (2025)
EmbedLLM: Learning Compact Representations of Large Language Models
by: Zhuang, Richard, et al.
Published: (2024)
by: Zhuang, Richard, et al.
Published: (2024)
Understanding and Mitigating Dataset Corruption in LLM Steering
by: Anderson, Cullen, et al.
Published: (2026)
by: Anderson, Cullen, et al.
Published: (2026)
Distribution-Aware Reward: Reinforcement Learning over Predictive Distributions for LLM Regression
by: Park, Jungsoo, et al.
Published: (2026)
by: Park, Jungsoo, et al.
Published: (2026)
Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks
by: Li, Miaomiao, et al.
Published: (2025)
by: Li, Miaomiao, et al.
Published: (2025)
From Exact Hits to Close Enough: Semantic Caching for LLM Embeddings
by: Biton, Dvir David, et al.
Published: (2026)
by: Biton, Dvir David, et al.
Published: (2026)
Understanding the Performance and Estimating the Cost of LLM Fine-Tuning
by: Xia, Yuchen, et al.
Published: (2024)
by: Xia, Yuchen, et al.
Published: (2024)
Bridging Human and LLM Judgments: Understanding and Narrowing the Gap
by: Polo, Felipe Maia, et al.
Published: (2025)
by: Polo, Felipe Maia, et al.
Published: (2025)
LLM-Guided Indoor Navigation with Multimodal Map Understanding
by: Coffrini, Alberto, et al.
Published: (2025)
by: Coffrini, Alberto, et al.
Published: (2025)
Evaluating LLM Understanding via Structured Tabular Decision Simulations
by: Li, Sichao, et al.
Published: (2025)
by: Li, Sichao, 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)
Think-Augmented Function Calling: Improving LLM Parameter Accuracy Through Embedded Reasoning
by: Wei, Lei, et al.
Published: (2026)
by: Wei, Lei, et al.
Published: (2026)
RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning
by: Wang, Zihan, et al.
Published: (2025)
by: Wang, Zihan, et al.
Published: (2025)
Instructional Segment Embedding: Improving LLM Safety with Instruction Hierarchy
by: Wu, Tong, et al.
Published: (2024)
by: Wu, Tong, et al.
Published: (2024)
Understand What LLM Needs: Dual Preference Alignment for Retrieval-Augmented Generation
by: Dong, Guanting, et al.
Published: (2024)
by: Dong, Guanting, et al.
Published: (2024)
Too Long, Didn't Model: Decomposing LLM Long-Context Understanding With Novels
by: Hamilton, Sil, et al.
Published: (2025)
by: Hamilton, Sil, et al.
Published: (2025)
Performance Prediction for Large Systems via Text-to-Text Regression
by: Akhauri, Yash, et al.
Published: (2025)
by: Akhauri, Yash, et al.
Published: (2025)
A General Framework for Producing Interpretable Semantic Text Embeddings
by: Sun, Yiqun, et al.
Published: (2024)
by: Sun, Yiqun, et al.
Published: (2024)
LLM-Assisted Content Conditional Debiasing for Fair Text Embedding
by: Deng, Wenlong, et al.
Published: (2024)
by: Deng, Wenlong, et al.
Published: (2024)
A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware Demonstration
by: Cui, Yingqian, et al.
Published: (2024)
by: Cui, Yingqian, et al.
Published: (2024)
Understanding Emergent Abilities of Language Models from the Loss Perspective
by: Du, Zhengxiao, et al.
Published: (2024)
by: Du, Zhengxiao, et al.
Published: (2024)
Clover: Regressive Lightweight Speculative Decoding with Sequential Knowledge
by: Xiao, Bin, et al.
Published: (2024)
by: Xiao, Bin, et al.
Published: (2024)
QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving
by: Lin, Yujun, et al.
Published: (2024)
by: Lin, Yujun, et al.
Published: (2024)
Explore Briefly, Then Decide: Mitigating LLM Overthinking via Cumulative Entropy Regulation
by: Bin, Yi, et al.
Published: (2025)
by: Bin, Yi, et al.
Published: (2025)
MPO: Boosting LLM Agents with Meta Plan Optimization
by: Xiong, Weimin, et al.
Published: (2025)
by: Xiong, Weimin, et al.
Published: (2025)
From Reasoning Chains to Verifiable Subproblems: Curriculum Reinforcement Learning Enables Credit Assignment for LLM Reasoning
by: Jiang, Xitai, et al.
Published: (2026)
by: Jiang, Xitai, et al.
Published: (2026)
dLLM: Simple Diffusion Language Modeling
by: Zhou, Zhanhui, et al.
Published: (2026)
by: Zhou, Zhanhui, et al.
Published: (2026)
Similar Items
-
Decoding-based Regression
by: Song, Xingyou, et al.
Published: (2025) -
OmniPred: Language Models as Universal Regressors
by: Song, Xingyou, et al.
Published: (2024) -
Regression Language Models for Code
by: Akhauri, Yash, et al.
Published: (2025) -
Language Model Embeddings Can Be Sufficient for Bayesian Optimization
by: Nguyen, Tung, et al.
Published: (2024) -
Understanding the Effects of RLHF on LLM Generalisation and Diversity
by: Kirk, Robert, et al.
Published: (2023)