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Christian Bauckhage

4 accepted papers

2025

Resource-Efficient Anonymization of Textual Data via Knowledge Distillation from Large Language Models

COLING 2025industry

Protecting personal and sensitive information in textual data is increasingly crucial, especially when leveraging large language models (LLMs) that may pose privacy risks due to their API-based access. We introduce a novel approach and pipeline for anonymizing text across arbitrary domains without t…

Cited by 0SourcePDFScholar
2023

A New Aligned Simple German Corpus

ACL 2023long

“Leichte Sprache”, the German counterpart to Simple English, is a regulated language aiming to facilitate complex written language that would otherwise stay inaccessible to different groups of people. We present a new sentence-aligned monolingual corpus for Simple German – German. It contains multip…

2023

Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

ICLR 2023top-25%

We tackle the problem of aligning pre-trained large language models (LMs) with human preferences. If we view text generation as a sequential decision-making problem, reinforcement learning (RL) appears to be a natural conceptual framework. However, using RL for LM-based generation faces empirical ch…

2021

Learning Deep Generative Models for Queuing Systems

AAAI 2021technical

Modern society is heavily dependent on large scale client-server systems with applications ranging from Internet and Communication Services to sophisticated logistics and deployment of goods. To maintain and improve such a system, a careful study of client and server dynamics is needed –…

Cited by 13SourcePDFScholar