activity
20202026
most citedTSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning

44 citations · 111 across the 45 of their papers we have counts for

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Showing 2024Show all

15 papers · 1 filter

cs.LG2024

Variational Model Merging for Pareto Front Estimation in Multitask Finetuning

Hugo Monzón Maldonado, Nico Daheim, Thomas Möllenhoff +2

Pareto fronts are useful to find good task-mixing strategies for multitask finetuning, but they are also costly to compute. To reduce costs, recent works have used existing model m…

cs.CL2024

The Lou Dataset -- Exploring the Impact of Gender-Fair Language in German Text Classification

Andreas Waldis, Joel Birrer, Anne Lauscher +1

Gender-fair language, an evolving German linguistic variation, fosters inclusion by addressing all genders or using neutral forms. Nevertheless, there is a significant lack of reso…

cs.AI2024

Problem Solving Through Human-AI Preference-Based Cooperation

Subhabrata Dutta, Timo Kaufmann, Goran Glavaš +7

While there is a widespread belief that artificial general intelligence (AGI) -- or even superhuman AI -- is imminent, complex problems in expert domains are far from being solved.…

cs.CL2024

Overview of PerpectiveArg2024: The First Shared Task on Perspective Argument Retrieval

Neele Falk, Andreas Waldis, Iryna Gurevych

Argument retrieval is the task of finding relevant arguments for a given query. While existing approaches rely solely on the semantic alignment of queries and arguments, this first…

cs.CL2024

Stepwise Verification and Remediation of Student Reasoning Errors with Large Language Model Tutors

Nico Daheim, Jakub Macina, Manu Kapur +2

Large language models (LLMs) present an opportunity to scale high-quality personalized education to all. A promising approach towards this means is to build dialog tutoring models…

cs.CL2024

Modular Sentence Encoders: Separating Language Specialization from Cross-Lingual Alignment

Yongxin Huang, Kexin Wang, Goran Glavaš +1

Multilingual sentence encoders (MSEs) are commonly obtained by training multilingual language models to map sentences from different languages into a shared semantic space. As such…

cs.CL2024

Constrained C-Test Generation via Mixed-Integer Programming

Ji-Ung Lee, Marc E. Pfetsch, Iryna Gurevych

This work proposes a novel method to generate C-Tests; a deviated form of cloze tests (a gap filling exercise) where only the last part of a word is turned into a gap. In contrast…

cs.CL2024

Holmes: A Benchmark to Assess the Linguistic Competence of Language Models

Andreas Waldis, Yotam Perlitz, Leshem Choshen +2

We introduce Holmes, a new benchmark designed to assess language models (LMs) linguistic competence - their unconscious understanding of linguistic phenomena. Specifically, we use…

cs.CL2024

Socratic Reasoning Improves Positive Text Rewriting

Anmol Goel, Nico Daheim, Christian Montag +1

Reframing a negative into a positive thought is at the crux of several cognitive approaches to mental health and psychotherapy that could be made more accessible by large language…

cs.CL2024★ 6 cited

Zero-shot Sentiment Analysis in Low-Resource Languages Using a Multilingual Sentiment Lexicon

Fajri Koto, Tilman Beck, Zeerak Talat +2

Improving multilingual language models capabilities in low-resource languages is generally difficult due to the scarcity of large-scale data in those languages. In this paper, we r…

cs.CL2024★ 1 cited

Dive into the Chasm: Probing the Gap between In- and Cross-Topic Generalization

Andreas Waldis, Yufang Hou, Iryna Gurevych

Pre-trained language models (LMs) perform well in In-Topic setups, where training and testing data come from the same topics. However, they face challenges in Cross-Topic scenarios…

cs.LG2024★ 3 cited

Variational Learning is Effective for Large Deep Networks

Yuesong Shen, Nico Daheim, Bai Cong +8

We give extensive empirical evidence against the common belief that variational learning is ineffective for large neural networks. We show that an optimizer called Improved Variati…

cs.CL2024

Triple-Encoders: Representations That Fire Together, Wire Together

Justus-Jonas Erker, Florian Mai, Nils Reimers +2

Search-based dialog models typically re-encode the dialog history at every turn, incurring high cost. Curved Contrastive Learning, a representation learning method that encodes rel…

cs.CL2024

Document Structure in Long Document Transformers

Jan Buchmann, Max Eichler, Jan-Micha Bodensohn +2

Long documents often exhibit structure with hierarchically organized elements of different functions, such as section headers and paragraphs. Despite the omnipresence of document s…

cs.CL2024

Code Prompting Elicits Conditional Reasoning Abilities in Text+Code LLMs

Haritz Puerto, Martin Tutek, Somak Aditya +2

Reasoning is a fundamental component of language understanding. Recent prompting techniques, such as chain of thought, have consistently improved LLMs' performance on various reaso…