1 citations · 2 across the 7 of their papers we have counts for
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TeachGrade: Training-Free Short Answer Scoring with Teacher Evidence
Jinhao Yan, Zhihong Shen, Shengjie Wang +4
Multi-subject, multi-step scoring requires consistent partial credit across grading conventions. We introduce TeachGrade, a training-free framework using teacher-graded examples. T…
DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models
Yilei Wang, Jiaxin Gan, Kexuan Zhang +3
Sequence labeling is a fine-grained information extraction task, yet existing large language model-based approaches suffer from insufficient domain alignment and low inference effi…
Heterogeneous Adaptive Policy Optimization: Tailoring Optimization to Every Token's Nature
Zheng Liu, Mengjie Liu, Siwei Wen +4
Using entropy as a measure of heterogeneity to guide optimization has emerged as a crucial research direction in Reinforcement Learning for LLMs. However, existing methods typicall…
PilotRL: Training Language Model Agents via Global Planning-Guided Progressive Reinforcement Learning
Keer Lu, Chong Chen, Bin Cui +2
Large Language Models (LLMs) have shown remarkable advancements in tackling agent-oriented tasks. Despite their potential, existing work faces challenges when deploying LLMs in age…
SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models
Peichao Lai, Kexuan Zhang, Yi Lin +8
Subjective Answer Grading (SAG) plays a crucial role in education, standardized testing, and automated assessment systems, particularly for evaluating short-form responses in Short…
Enhancing Unsupervised Sentence Embeddings via Knowledge-Driven Data Augmentation and Gaussian-Decayed Contrastive Learning
Peichao Lai, Zhengfeng Zhang, Wentao Zhang +2
Recently, using large language models (LLMs) for data augmentation has led to considerable improvements in unsupervised sentence embedding models. However, existing methods encount…