arXiv Machine Learning

Enhancing Automated Essay Scoring With Three Techniques: Two-Stage Fine-Tuning, Score Alignment, and Self-Training

arXiv:2602. 01747v2 Announce Type: replace-cross Abstract: Automated Essay Scoring (AES) plays a crucial role in education by providing scalable and efficient assessment tools.

arXiv Machine Learning

Jun 10

The Order Matters: Sequential Fine-Tuning of LLaMA for Coherent Automated Essay Scoring

arXiv:2606. 10327v1 Announce Type: cross Abstract: Automated Essay Scoring (AES) systems must judge interdependent discourse elements (e.

By Ali Keramati, Mark Warschauer

llms nlp fine-tuning efficiency

arXiv AI

Jul 22

Beyond Score Prediction: LLM-Based Essay Scoring and Feedback Generation via Reinforcement Learning with Rubric Rewards

arXiv:2607. 19219v1 Announce Type: cross Abstract: Large language models (LLMs) have been widely applied to automated essay scoring (AES) and automated feedback generation (AFG).

By Xuefeng Jin, Jiashuo Zhang, Teng Cao, Bin Yang

llms reinforcement-learning fine-tuning benchmarks

arXiv AI

Jun 19

From Texts to Scores: Tracing the Emergence of Essay Quality Representations in Large Language Models

arXiv:2606. 20152v1 Announce Type: cross Abstract: Recent advances in Large Language Models (LLMs) have substantially transformed Automated Essay Scoring (AES), yet the internal mechanisms underlying LLM-based scoring remain poorly understood.

By Jiaxu Zuo, Mu You, Kaixin Lan, Tao Fang, Yujia Huo, Henghua Shen, Lidia S. Chao, Derek F. Wong

llms safety

Hugging Face Trending Papers

Jul 21

Beyond Score Prediction: LLM-Based Essay Scoring and Feedback Generation via Reinforcement Learning with Rubric Rewards

Large language models (LLMs) have been widely applied to automated essay scoring (AES) and automated feedback generation (AFG). However, existing studies rely primarily on prompt engineering or supervised fine-tuning, while systematic research on reinforcement learning (RL) post-training and automated evaluation of feedback quality remains limited.

llms reinforcement-learning fine-tuning benchmarks

arXiv Machine Learning

Jul 20

Cost-efficient generative AI summarization for scalable automated essay scoring in educational assessment

arXiv:2607. 15829v1 Announce Type: cross Abstract: Automated essay scoring (AES) enables scalable assessment and timely feedback but remains challenged by transformer input-length limitations, which can cause information loss when processing long essays.

By Haowei Hua

llms nlp benchmarks safety

arXiv AI

Jul 17

WrAFT: a Modularized Automated Writing Evaluation System for Argumentative Essays

arXiv:2607. 14524v1 Announce Type: new Abstract: This study presents WrAFT, a Writing Assessment and Feedback Tool, that delivers both accurate and reliable scores and effective comprehensive feedback to argumentative essays.

By Adnan Labib, Yixuan Huang, Jiahui Wu, John Maurice Gayed, Zheng Yuan, Qiao Wang

llms fine-tuning benchmarks

arXiv AI

Jun 3

AnyAudio-Judge: A Dynamic Rubric-Based Benchmark and Evaluator for Audio Instruction Following

arXiv:2606. 03116v1 Announce Type: cross Abstract: The rapid advancement of instruction-guided audio generation has highlighted the critical need for robust alignment evaluation.

By Haitao Li, Tian Tan, Yuguang Yang, Shan Yang, Xie Chen

llms reinforcement-learning fine-tuning benchmarks safety

arXiv Machine Learning

Jun 3

Alignment-Aware Decoding

arXiv:2509. 26169v2 Announce Type: replace Abstract: Alignment of large language models remains a central challenge in natural language processing.

By Fr\'ed\'eric Berdoz, Luca A. Lanzend\"orfer, Ren\'e Caky, Roger Wattenhofer

llms nlp reinforcement-learning benchmarks safety

arXiv AI

Jun 24

SURGELLM: Rethinking Multi-Task Evaluation through Task-Aware Feature Gating with Class-Balanced Normalization

arXiv:2606. 24259v1 Announce Type: cross Abstract: Fine-tuned encoders deployed across heterogeneous NLP tasks face three compounding problems: mismatched inductive biases, class-imbalance corruption of feature statistics, and no mechanism to condition attention on external lexical knowledge.

By Noor Islam S. Mohammad, Ulug Bayazit

llms nlp fine-tuning efficiency safety

arXiv AI

Jul 7

Safe Inference-Time Alignment via Lagrangian Reward Augmentation

arXiv:2607. 02781v1 Announce Type: cross Abstract: Inference-time alignment steers a frozen language model during decoding using auxiliary reward signals, avoiding the cost of repeated weight updates.

By Yaswanth Chittepu, Ativ Joshi, Sohini Chintala, Scott Niekum

llms rag reinforcement-learning fine-tuning safety

arXiv AI

Aug 10

Mitigating Scoring Bias in LLM-as-a-Judge via Random Number Generation

arXiv:2608. 05726v1 Announce Type: cross Abstract: Large Language Models (LLMs) are often used as evaluators of text quality, known as LLM-as-a-Judge, which can outperform conventional automatic evaluation metrics that rely on reference texts.

By Yuma Asato, Kiyoaki Shirai, Natthawut Kertkeidkachorn

llms nlp safety

arXiv AI

Jul 7

Aligning Language Models with Selective Prediction

arXiv:2607. 03528v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as critical decision-making components in high-stakes real-world AI systems, rendering LLM reliability a foremost practical concern.

By Gaoxiang Luo, Yifan Wu, Sinian Zhang, Aryan Deshwal, Ju Sun

llms reinforcement-learning safety

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