mlsanityData to 7 Oct 2026

BenGER Platform: A Collaborative Web Platform for End-to-End Benchmarking of German Legal Tasks

arXiv 2604.13583 ↗First posted 15 Apr 2026cs.CL cs.AIcited by 1

On the map: LLM reasoning → Reasoning for agents, planning and code

Abstract (arXiv)

Evaluating large language models (LLMs) for legal reasoning requires workflows that span task design, expert annotation, model execution, and metric-based evaluation. In practice, these steps are split across platforms and scripts, limiting transparency, reproducibility, and participation by non-technical legal experts. We present the BenGER (Benchmark for German Law) framework, an open-source web platform that integrates task creation, collaborative annotation, configurable LLM runs, and evaluation with lexical, semantic, factual, and judge-based metrics. BenGER supports multi-organization projects with tenant isolation and role-based access control, and can optionally provide formative, reference-grounded feedback to annotators. We will demonstrate a live deployment showing end-to-end benchmark creation and analysis.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning. Builds on 0 of its 7 references that are in the map. First posted on arXiv 15 Apr 2026.

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  1. 2023LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models
  2. 2026Multi-Legal-Bench: Evaluating LLMs on Legal Reasoning Across Jurisdictions, Languages, and Legal Traditions
  3. 2023One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support
  4. 2025LeMAJ (Legal LLM-as-a-Judge): Bridging Legal Reasoning and LLM Evaluation
  5. 2023LawBench: Benchmarking Legal Knowledge of Large Language Models
  6. 2025Benchmarking Multi-Step Legal Reasoning and Analyzing Chain-of-Thought Effects in Large Language Models
  7. 2026OpenExempt: A Diagnostic Benchmark for Legal Reasoning and a Framework for Creating Custom Benchmarks on Demand
  8. 2026Evaluation of Large Language Models in Legal Applications: Challenges, Methods, and Future Directions