SRJudge: Empowering Large Language Models with Selective Reasoning for Fine-Grained Knowledge Concept Tagging

arXiv:2609.36982 · cs.CL, cs.AI · Submitted 2026-09-29 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-09-29

Updated: 2026-09-29

Code: https://github.com/Nicozwy/SRJudge

Terminology

• Pruning — 15× in this paper · explained in 4 episodes
• GRPO — 13× in this paper · explained in 6 episodes
• Accuracy — 11× in this paper · explained in 1 episode
• F1 Score — 8× in this paper · explained in 3 episodes
• Reinforcement Learning — 8× in this paper · explained in 4 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Fine-Tuning — 5× in this paper · explained in 5 episodes
• Reward Function — 4× in this paper · explained in 2 episodes
• Ablation study — 3× in this paper · explained in 1 episode
• Contrastive Learning — 3× in this paper · explained in 5 episodes
• Ensemble Learning — 2× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Semantic Understanding — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Active Exploration — 1× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Contextual Understanding — 1× in this paper · explained in 2 episodes
• Feature Engineering — 1× in this paper · explained in 3 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Knowledge Tracing Models — 1× in this paper · explained in 2 episodes
• Knowledge graphs — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Multi-agent Collaboration — 1× in this paper · explained in 2 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Semantic Similarity — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• GPT-4 Technical Report
• Qwen Technical Report
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• Conan-embedding: General Text Embedding with More and Better Negative Samples
• RoBERTa: A Robustly Optimized BERT Pretraining Approach
• Automated Knowledge Concept Annotation and Question Representation Learning for Knowledge Tracing
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• LLaMA: Open and Efficient Foundation Language Models

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