ArguLens: An Open-Source System for Automated Essay Scoring and Label-Aware Feedback Generation
Most automated essay scoring (AES) systems output a single holistic score without interpretable evidence and rely on closed APIs that introduce data privacy and cost barriers. We present ArguLens, an opensource, locally deployable system that decomposes AES into three decoupled components: a discourse-move classifier (Qwen2.5-7B-Instruct fine-tuned with LoRA on PERSUADE 2.0), a grade-independent LightGBM scorer over 31 linguistic and discourse features, and a label-aware feedback generator served through vLLM with a Qwen2.5-14BInstruct backbone. A Gradio web UI exposes pluggable inference backends and supports single-essay and batch scoring with downloadable per-essay breakdowns. On an es...
| Authors | Weiran Wang, Hongxiang Shi, Huitao Tang et al. |
|---|---|
| Primary category | cs.CL |
| Published | 18 August 2026 |
| Last updated at source | 18 August 2026 |
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