I am a final-year Ph.D. candidate in Machine Learning & Natural Language Processing at UKP Lab in TU Darmstadt, supervised by Prof. Iryna Gurevych. My research focuses on advancing reasoning and enhancing explainability in large language models, aiming to develop next-generation AI systems capable of helping humans solving complex tasks. During my Ph.D., I have interned at Parameter Lab, where we worked with Naver AI on trustworthy AI. Before my Ph.D., I worked at the Coleridge Initiative, where I co-organized the Kaggle Competition Show US the Data. I got my master's degree from the School of Computing at KAIST, where I was a research assistant at IR&NLP Lab and was advised by Professor Sung-Hyon Myaeng.
Teaching LLaMAs how to "think"
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@UKPLab, TU Darmstadt
- Germany
- https://haritzpuerto.github.io
Highlights
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parameterlab/c-seo-bench
parameterlab/c-seo-bench PublicSource code of "C-SEO Bench: Does Conversational SEO Work?" NeurIPS D&B 2025
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UKPLab/acl2025-diverse-cot
UKPLab/acl2025-diverse-cot PublicCode for the 2025 ACL publication "Fine-Tuning on Diverse Reasoning Chains Drives Within-Inference CoT Refinement in LLMs"
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parameterlab/mia-scaling
parameterlab/mia-scaling PublicSource code of NAACL 2025 Findings "Scaling Up Membership Inference: When and How Attacks Succeed on Large Language Models"
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UKPLab/emnlp2024-code-prompting
UKPLab/emnlp2024-code-prompting PublicCode Prompting Elicits Conditional Reasoning Abilities in Text+Code LLMs. EMNLP 2024
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MetaQA
MetaQA PublicForked from UKPLab/MetaQA
MetaQA: Combining Expert Agents for Multi-Skill Question Answering
Python
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