LexReward: A Taxonomy-Driven Reward Framework for Legal Language Models

arXiv:2609.39071 · cs.CL · Submitted 2026-09-30 · Read on arXiv

cs.CL

Submitted: 2026-09-30

Updated: 2026-09-30

Code: https://github.com/thunlp/LexReward

Terminology

• GRPO — 22× in this paper · explained in 6 episodes
• Accuracy — 10× in this paper · explained in 1 episode
• Reinforcement Learning — 8× in this paper · explained in 4 episodes
• Redundancy — 7× in this paper · explained in 2 episodes
• Benchmark — 6× in this paper · explained in 2 episodes
• Aggregation — 3× in this paper · explained in 1 episode
• Calibration — 3× in this paper · explained in 7 episodes
• LLM judge — 3× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 3× in this paper · explained in 3 episodes
• Reward Function — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Actor — 2× in this paper · explained in 3 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Direct Preference Optimization — 2× in this paper
• Direct Preference Optimization (DPO) — 2× in this paper · explained in 9 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Group Relative Policy Optimization — 2× in this paper
• Group Relative Policy Optimization (GRPO) — 2× in this paper · explained in 5 episodes
• Test-Time Scaling (TTS) — 2× in this paper · explained in 2 episodes
• Test-time Scaling — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Alignment Methods — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Core — 1× in this paper · explained in 2 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Information Gain — 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
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes

Sources

• SCPRM: A Schema-aware Cumulative Process Reward Model for Knowledge Graph Question Answering
• Gemma 4 Technical Report
• Editing Models with Task Arithmetic
• LexEval: A Comprehensive Chinese Legal Benchmark for Evaluating Large Language Models
• Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy
• The Llama 3 Herd of Models
• GPT-4o System Card
• OpenHowNet: An Open Sememe-based Lexical Knowledge Base
• Qwen3 Technical Report
• Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts
• Lawformer: A Pre-trained Language Model for Chinese Legal Long Documents

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