Cover Image

Query-Conditioned Test-Time Self-Training for Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Song, Chaehee, Seo, Minseok, Seong, Yeeun, Kim, Doyi, Kim, Changick
Format:	Preprint
Published:	2026
Subjects:	Computation and Language Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Self-Training Elicits Concise Reasoning in Large Language Models
by: Munkhbat, Tergel, et al.
Published: (2025)

Aligning Large Language Models via Fine-grained Supervision
by: Xu, Dehong, et al.
Published: (2024)

Aligning Large Language Models by On-Policy Self-Judgment
by: Lee, Sangkyu, et al.
Published: (2024)

Rethinking the Role of Proxy Rewards in Language Model Alignment
by: Kim, Sungdong, et al.
Published: (2024)

Station2Radar: query conditioned gaussian splatting for precipitation field
by: Kim, Doyi, et al.
Published: (2026)

Self-Trained Verification for Training- and Test-Time Self-Improvement
by: Wu, Chen Henry, et al.
Published: (2026)

Test-Time Learning for Large Language Models
by: Hu, Jinwu, et al.
Published: (2025)

Auto-Intent: Automated Intent Discovery and Self-Exploration for Large Language Model Web Agents
by: Kim, Jaekyeom, et al.
Published: (2024)

Non-linear Interventions on Large Language Models
by: Kim, Sangwoo
Published: (2026)

Difficulty-aware Balancing Margin Loss for Long-tailed Recognition
by: Son, Minseok, et al.
Published: (2024)

Nevermind: Instruction Override and Moderation in Large Language Models
by: Kim, Edward
Published: (2024)

Training Reasoning Models on Saturated Problems via Failure-Prefix Conditioning
by: Kim, Minwu, et al.
Published: (2026)

DiTTO-LLM: Framework for Discovering Topic-based Technology Opportunities via Large Language Model
by: Kim, Wonyoung, et al.
Published: (2025)

The Surprising Effectiveness of Test-Time Training for Few-Shot Learning
by: Akyürek, Ekin, et al.
Published: (2024)

Uncovering Emergent Physics Representations Learned In-Context by Large Language Models
by: Song, Yeongwoo, et al.
Published: (2025)

BiasJailbreak:Analyzing Ethical Biases and Jailbreak Vulnerabilities in Large Language Models
by: Lee, Isack, et al.
Published: (2024)

Provable Scaling Laws for the Test-Time Compute of Large Language Models
by: Chen, Yanxi, et al.
Published: (2024)

ERBench: An Entity-Relationship based Automatically Verifiable Hallucination Benchmark for Large Language Models
by: Oh, Jio, et al.
Published: (2024)

SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling
by: Kim, Dahyun, et al.
Published: (2023)

Personalizing Large Language Models using Retrieval Augmented Generation and Knowledge Graph
by: Prahlad, Deeksha, et al.
Published: (2025)

In-Place Test-Time Training
by: Feng, Guhao, et al.
Published: (2026)

AdaSTaR: Adaptive Data Sampling for Training Self-Taught Reasoners
by: Koh, Woosung, et al.
Published: (2025)

IPCGRL: Language-Instructed Reinforcement Learning for Procedural Level Generation
by: Baek, In-Chang, et al.
Published: (2025)

TLPO: Token-Level Policy Optimization for Mitigating Language Confusion in Large Language Models
by: Choo, Jinho, et al.
Published: (2026)

AI-Augmented Surveys: Leveraging Large Language Models and Surveys for Opinion Prediction
by: Kim, Junsol, et al.
Published: (2023)

Scalable Best-of-N Selection for Large Language Models via Self-Certainty
by: Kang, Zhewei, et al.
Published: (2025)

TableTime: Reformulating Time Series Classification as Training-Free Table Understanding with Large Language Models
by: Wang, Jiahao, et al.
Published: (2024)

Align to Structure: Aligning Large Language Models with Structural Information
by: Kim, Zae Myung, et al.
Published: (2025)

Sliding Window Attention Training for Efficient Large Language Models
by: Fu, Zichuan, et al.
Published: (2025)

Graph Elicitation for Guiding Multi-Step Reasoning in Large Language Models
by: Park, Jinyoung, et al.
Published: (2023)

STARLING: Self-supervised Training of Text-based Reinforcement Learning Agent with Large Language Models
by: Basavatia, Shreyas, et al.
Published: (2024)

ProgCo: Program Helps Self-Correction of Large Language Models
by: Song, Xiaoshuai, et al.
Published: (2025)

Calibrating Large Language Models Using Their Generations Only
by: Ulmer, Dennis, et al.
Published: (2024)

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
by: Xiao, Guangxuan, et al.
Published: (2022)

Enhancing LLM Reasoning via Critique Models with Test-Time and Training-Time Supervision
by: Xi, Zhiheng, et al.
Published: (2024)

MesaNet: Sequence Modeling by Locally Optimal Test-Time Training
by: von Oswald, Johannes, et al.
Published: (2025)

Detecting Training Data of Large Language Models via Expectation Maximization
by: Kim, Gyuwan, et al.
Published: (2024)

Training Optimal Large Diffusion Language Models
by: Ni, Jinjie, et al.
Published: (2025)

Mode-Conditioning Unlocks Superior Test-Time Scaling
by: Wu, Chen Henry, et al.
Published: (2025)

Regurgitative Training: The Value of Real Data in Training Large Language Models
by: Zhang, Jinghui, et al.
Published: (2024)