Cover Image

Feedback-to-Rubrics: Can We Learn Expert Criteria from Inline Comments?

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yoshida, Kotaro, Kuroki, So, Imajuku, Yuki, Nakamura, Taishi, Iwai, Ryunosuke, Goda, Haruki, Akiba, Takuya
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search
by: Inoue, Yuichi, et al.
Published: (2025)

Agent Skill Acquisition for Large Language Models via CycleQD
by: Kuroki, So, et al.
Published: (2024)

Drop-Upcycling: Training Sparse Mixture of Experts with Partial Re-initialization
by: Nakamura, Taishi, et al.
Published: (2025)

ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution
by: Lange, Robert Tjarko, et al.
Published: (2025)

Robust Invariant Representation Learning by Distribution Extrapolation
by: Yoshida, Kotaro, et al.
Published: (2025)

How Does Preconditioning Guide Feature Learning in Deep Neural Networks?
by: Yoshida, Kotaro, et al.
Published: (2025)

Multi-Play Combinatorial Semi-Bandit Problem
by: Nakamura, Shintaro, et al.
Published: (2025)

Balancing Speed and Stability: The Trade-offs of FP8 vs. BF16 Training in LLMs
by: Fujii, Kazuki, et al.
Published: (2024)

Towards Understanding Variants of Invariant Risk Minimization through the Lens of Calibration
by: Yoshida, Kotaro, et al.
Published: (2024)

Sudoku-Bench: Evaluating creative reasoning with Sudoku variants
by: Seely, Jeffrey, et al.
Published: (2025)

UnMaskFork: Test-Time Scaling for Masked Diffusion via Deterministic Action Branching
by: Misaki, Kou, et al.
Published: (2026)

Optimal Sparsity of Mixture-of-Experts Language Models for Reasoning Tasks
by: Nakamura, Taishi, et al.
Published: (2025)

On the Optimal Reasoning Length for RL-Trained Language Models
by: Nohara, Daisuke, et al.
Published: (2026)

Auto-Rubric: Learning From Implicit Weights to Explicit Rubrics for Reward Modeling
by: Xie, Lipeng, et al.
Published: (2025)

KAME: Tandem Architecture for Enhancing Knowledge in Real-Time Speech-to-Speech Conversational AI
by: Kuroki, So, et al.
Published: (2025)

DiffusionBlocks: Block-wise Neural Network Training via Diffusion Interpretation
by: Shing, Makoto, et al.
Published: (2025)

Dynamic Structure Estimation from Bandit Feedback using Nonvanishing Exponential Sums
by: Ohnishi, Motoya, et al.
Published: (2022)

Sequence-Aware Inline Measurement Attribution for Good-Bad Wafer Diagnosis
by: Miyaguchi, Kohei, et al.
Published: (2025)

Can We Detect Failures Without Failure Data? Uncertainty-Aware Runtime Failure Detection for Imitation Learning Policies
by: Xu, Chen, et al.
Published: (2025)

On What We Can Learn from Low-Resolution Data
by: Frehr, Theresa Dahl, et al.
Published: (2026)

What Can We Learn From MIMO Graph Convolutions?
by: Roth, Andreas, et al.
Published: (2025)

Reinforcement Learning with Rubric Anchors
by: Huang, Zenan, et al.
Published: (2025)

Test-Time Alignment of LLMs via Sampling-Based Optimal Control in pre-logit space
by: Kanai, Sekitoshi, et al.
Published: (2025)

AMARIS: A Memory-Augmented Rubric Improvement System for Rubric-Based Reinforcement Learning
by: Wu, Peilin, et al.
Published: (2026)

Sequential Decision-Making for Inline Text Autocomplete
by: Chitnis, Rohan, et al.
Published: (2024)

Off-Policy Evaluation and Learning for Matching Markets
by: Hayashi, Yudai, et al.
Published: (2025)

What Can We Learn from State Space Models for Machine Learning on Graphs?
by: Huang, Yinan, et al.
Published: (2024)

ODIA: Oriented Distillation for Inline Acceleration of LLM-based Function Calling
by: Zhang, Hanlong, et al.
Published: (2025)

Focal Reward: Balanced Reinforcement Learning under Rubric-Based Rewards
by: Huang, Yu, et al.
Published: (2026)

ALE-Bench: A Benchmark for Long-Horizon Objective-Driven Algorithm Engineering
by: Imajuku, Yuki, et al.
Published: (2025)

Learning to Judge: LLMs Designing and Applying Evaluation Rubrics
by: Siro, Clemencia, et al.
Published: (2026)

PCM Selector: Penalized Covariate-Mediator Selection Operator for Evaluating Linear Causal Effects
by: Nanmo, Hisayoshi, et al.
Published: (2024)

Bayesian Meta-Learning with Expert Feedback for Task-Shift Adaptation through Causal Embeddings
by: Mäkinen, Lotta, et al.
Published: (2026)

RubricEM: Meta-RL with Rubric-guided Policy Decomposition beyond Verifiable Rewards
by: Li, Gaotang, et al.
Published: (2026)

An Empirical Study of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration
by: Naganuma, Hiroki, et al.
Published: (2023)

DisTaC: Conditioning Task Vectors via Distillation for Robust Model Merging
by: Yoshida, Kotaro, et al.
Published: (2025)

Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated Learning?
by: Ju, Peizhong, et al.
Published: (2024)

Step-wise Rubric Rewards for LLM Reasoning
by: Xie, Weichu, et al.
Published: (2026)

Agentic Rubrics as Contextual Verifiers for SWE Agents
by: Raghavendra, Mohit, et al.
Published: (2026)

Robust Reward Modeling via Causal Rubrics
by: Srivastava, Pragya, et al.
Published: (2025)