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Found 12 papers, 8 papers with code
UniHD@CL-SciSumm 2020: Citation Extraction as Search
This work presents the entry by the team from Heidelberg University in the CL-SciSumm 2020 shared task at the Scholarly Document Processing workshop at EMNLP 2020.
TICKing All the Boxes: Generated Checklists Improve LLM Evaluation and Generation
We then show that STICK (Self-TICK) can be used to improve generation quality across multiple benchmarks via self-refinement and Best-of-N selection.
On Leakage of Code Generation Evaluation Datasets
In this paper, we consider contamination by code generation test sets, in particular in their use in modern large language models.
How Does Quantization Affect Multilingual LLMs?
Quantization techniques are widely used to improve inference speed and deployment of large language models.
BLESS: Benchmarking Large Language Models on Sentence Simplification
Our performance benchmark will be available as a resource for the development of future TS methods and evaluation metrics.
Evaluating Factual Consistency of Texts with Semantic Role Labeling
We introduce SRLScore, a reference-free evaluation metric designed with text summarization in mind.
On the State of German (Abstractive) Text Summarization
We attribute poor evaluation quality to a variety of different factors, which are investigated in more detail in this work: A lack of qualitative (and diverse) gold data considered for training, understudied (and untreated) positional biases in some of the existing datasets, and the lack of easily accessible and streamlined pre-processing strategies or analysis tools.
UniHD at TSAR-2022 Shared Task: Is Compute All We Need for Lexical Simplification?
Previous state-of-the-art models for lexical simplification consist of complex pipelines with several components, each of which requires deep technical knowledge and fine-tuned interaction to achieve its full potential.
EUR-Lex-Sum: A Multi- and Cross-lingual Dataset for Long-form Summarization in the Legal Domain
Existing summarization datasets come with two main drawbacks: (1) They tend to focus on overly exposed domains, such as news articles or wiki-like texts, and (2) are primarily monolingual, with few multilingual datasets.
Klexikon: A German Dataset for Joint Summarization and Simplification
Traditionally, Text Simplification is treated as a monolingual translation task where sentences between source texts and their simplified counterparts are aligned for training.
Ranked #1 on
Text Summarization
on Klexikon
BERT got a Date: Introducing Transformers to Temporal Tagging
By supplementing training resources with weakly labeled data from rule-based systems, our model surpasses previous works in temporal tagging and type classification, especially on rare classes.
Ranked #1 on
Temporal Tagging
on TempEval-3
Structural Text Segmentation of Legal Documents
The growing complexity of legal cases has lead to an increasing interest in legal information retrieval systems that can effectively satisfy user-specific information needs.
