Cover Image

Causal LLM Routing: End-to-End Regret Minimization from Observational Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tsiourvas, Asterios, Sun, Wei, Perakis, Georgia
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Computation and Language Machine Learning Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Absorber LLM: Harnessing Causal Synchronization for Test-Time Training
by: Zhang, Zhixin, et al.
Published: (2026)

How Multimodal Integration Boost the Performance of LLM for Optimization: Case Study on Capacitated Vehicle Routing Problems
by: Huang, Yuxiao, et al.
Published: (2024)

Secure LLM Fine-Tuning via Safety-Aware Probing
by: Wu, Chengcan, et al.
Published: (2025)

Understanding Forgetting in LLM Supervised Fine-Tuning and Preference Learning -- A Convex Optimization Perspective
by: Fernando, Heshan, et al.
Published: (2024)

AI2STOW: End-to-End Deep Reinforcement Learning to Construct Master Stowage Plans under Demand Uncertainty
by: Van Twiller, Jaike, et al.
Published: (2025)

When and How Unlabeled Data Provably Improve In-Context Learning
by: Li, Yingcong, et al.
Published: (2025)

Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond
by: Li, Yingcong, et al.
Published: (2024)

Tight Mixed-Integer Optimization Formulations for Prescriptive Trees
by: Biggs, Max, et al.
Published: (2023)

ControlAgent: Automating Control System Design via Novel Integration of LLM Agents and Domain Expertise
by: Guo, Xingang, et al.
Published: (2024)

Muon Outperforms Adam in Tail-End Associative Memory Learning
by: Wang, Shuche, et al.
Published: (2025)

Solving General Natural-Language-Description Optimization Problems with Large Language Models
by: Zhang, Jihai, et al.
Published: (2024)

Adversarial Representation Engineering: A General Model Editing Framework for Large Language Models
by: Zhang, Yihao, et al.
Published: (2024)

Reinforcement Learning from Human Feedback with Active Queries
by: Ji, Kaixuan, et al.
Published: (2024)

Dynamic Orthogonal Continual Fine-tuning for Mitigating Catastrophic Forgettings
by: Zhang, Zhixin, et al.
Published: (2025)

DiaBlo: Diagonal Blocks Are Sufficient For Finetuning
by: Gurses, Selcuk, et al.
Published: (2025)

Gating is Weighting: Understanding Gated Linear Attention through In-context Learning
by: Li, Yingcong, et al.
Published: (2025)

One-Shot Safety Alignment for Large Language Models via Optimal Dualization
by: Huang, Xinmeng, et al.
Published: (2024)

Reward Collapse in Aligning Large Language Models
by: Song, Ziang, et al.
Published: (2023)

Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models
by: Gautam, Tanmay, et al.
Published: (2024)

Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers
by: Chen, Siyu, et al.
Published: (2024)

Variational Learning is Effective for Large Deep Networks
by: Shen, Yuesong, et al.
Published: (2024)

LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
by: Pan, Rui, et al.
Published: (2024)

Transformers as Support Vector Machines
by: Tarzanagh, Davoud Ataee, et al.
Published: (2023)

Mechanics of Next Token Prediction with Self-Attention
by: Li, Yingcong, et al.
Published: (2024)

When and Why SignSGD Outperforms SGD: A Theoretical Study Based on $\ell_1$-norm Lower Bounds
by: Tao, Hongyi, et al.
Published: (2026)

Leveraging Large Language Models for Solving Rare MIP Challenges
by: Wang, Teng, et al.
Published: (2024)

Exploring the Robustness of In-Context Learning with Noisy Labels
by: Cheng, Chen, et al.
Published: (2024)

ACING: Actor-Critic for Instruction Learning in Black-Box LLMs
by: Kharrat, Salma, et al.
Published: (2024)

Boosting Jailbreak Attack with Momentum
by: Zhang, Yihao, et al.
Published: (2024)

Wasserstein Distributionally Robust Regret Optimization for Reinforcement Learning from Human Feedback
by: Wang, Yikai, et al.
Published: (2026)

RouteExplainer: An Explanation Framework for Vehicle Routing Problem
by: Kikuta, Daisuke, et al.
Published: (2024)

Survey on Neural Routing Solvers
by: Ba, Yunpeng, et al.
Published: (2026)

RAPO: Risk-Aware Preference Optimization for Generalizable Safe Reasoning
by: Wei, Zeming, et al.
Published: (2026)

Sublinear Regret for a Class of Continuous-Time Linear-Quadratic Reinforcement Learning Problems
by: Huang, Yilie, et al.
Published: (2024)

Reinforcement Learning for Multi-Truck Vehicle Routing Problems
by: Levin, Joshua, et al.
Published: (2022)

Learning to Insert for Constructive Neural Vehicle Routing Solver
by: Luo, Fu, et al.
Published: (2025)

Towards Efficient Constraint Handling in Neural Solvers for Routing Problems
by: Bi, Jieyi, et al.
Published: (2026)

Federated Majorize-Minimization: Beyond Parameter Aggregation
by: Dieuleveut, Aymeric, et al.
Published: (2025)

PowerStep: Memory-Efficient Adaptive Optimization via $\ell_p$-Norm Steepest Descent
by: Lu, Yao, et al.
Published: (2026)

Soft-Radial Projection for Constrained End-to-End Learning
by: Schneider, Philipp J., et al.
Published: (2026)