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1.97 kB
| cff-version: 1.2.0 | |
| message: "If you use GDB in research, please cite as below." | |
| title: "When Empathy Misses the Goal: A Benchmark for Goal Displacement in LLM Advice" | |
| abstract: >- | |
| GDB is a 230-scenario benchmark for measuring goal displacement in | |
| large language models that provide advice: the substitution of warmth, | |
| reassurance, or non-directive encouragement for goal-advancing content | |
| when the latter is required. The release contains scenarios across nine domains, 4,134 | |
| human-scored model responses spanning 18 systems, and three supplementary | |
| probes (external rater portability, post-training stage decomposition, | |
| and a complexity-by-pressure factorial that dissociates displacement from | |
| social sycophancy). | |
| authors: | |
| - family-names: "Ariel" | |
| given-names: "Dean" | |
| affiliation: "Department of Family Medicine, Clalit Health Services, Tel Aviv District; Faculty of Medicine and Health Sciences, Tel Aviv University; Stein Faculty of Computer and Information Science, Ben-Gurion University of the Negev" | |
| - family-names: "Laban" | |
| given-names: "Guy" | |
| affiliation: "Department of Industrial Engineering and Management, Ben-Gurion University of the Negev" | |
| email: "laban@bgu.ac.il" | |
| version: "1.0.0" | |
| date-released: "2026-10-16" | |
| doi: "10.57967/hf/11042" | |
| license: "CC-BY-4.0" | |
| keywords: | |
| - "language models" | |
| - "evaluation" | |
| - "benchmark" | |
| - "goal displacement" | |
| - "alignment" | |
| - "RLHF" | |
| - "sycophancy" | |
| repository-code: "https://github.com/Guylaban/GDB" | |
| url: "https://huggingface.co/datasets/guylaban/gdb-benchmark" | |
| preferred-citation: | |
| type: conference-paper | |
| title: "When Empathy Misses the Goal: A Benchmark for Goal Displacement in LLM Advice" | |
| authors: | |
| - family-names: "Ariel" | |
| given-names: "Dean" | |
| - family-names: "Laban" | |
| given-names: "Guy" | |
| year: 2026 | |
| collection-title: "Proceedings of the 40th Conference on Neural Information Processing Systems (NeurIPS 2026), Track on Evaluations and Datasets" | |