4 citations · 5 across the 15 of their papers we have counts for
15 papers
OctoLong: Mid-Training On Cross-Repository Code Contexts Enhances Long-Context Modeling
Indraneil Paul, Falko Helm, Goran Glavaš +1
Context lengths of language models (LMs) have dramatically increased, driven by the demands for in-context learning, self-improvement, and long-horizon agentic workflows. However,…
Themis: Training Robust Multilingual Code Reward Models for Flexible Multi-Criteria Scoring
Indraneil Paul, Goran Glavaš, Iryna Gurevych
Reward models (RMs) have become an indispensable fixture of the language model (LM) post-training playbook, enabling policy alignment and test-time scaling. Research on the applica…
One Script Instead of Hundreds? On Pretraining Romanized Encoder Language Models
Benedikt Ebing, Lennart Keller, Goran Glavaš
Exposing latent lexical overlap, script romanization has emerged as an effective strategy for improving cross-lingual transfer (XLT) in multilingual language models (mLMs). Most pr…
TransAlign: Machine Translation Encoders are Strong Word Aligners, Too
Benedikt Ebing, Christian Goldschmied, Goran Glavaš
In the absence of sizable training data for most world languages and NLP tasks, translation-based strategies such as translate-test -- evaluating on noisy source language data tran…
The Devil Is in the Word Alignment Details: On Translation-Based Cross-Lingual Transfer for Token Classification Tasks
Benedikt Ebing, Goran Glavaš
Translation-based strategies for cross-lingual transfer XLT such as translate-train -- training on noisy target language data translated from the source language -- and translate-t…
ObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation Grounding
Indraneil Paul, Haoyi Yang, Goran Glavaš +2
Language models (LMs) have become a staple of the code-writing toolbox. Their pre-training recipe has, however, remained stagnant over recent years, barring the occasional changes…
SpeechTaxi: On Multilingual Semantic Speech Classification
Lennart Keller, Goran Glavaš
Recent advancements in multilingual speech encoding as well as transcription raise the question of the most effective approach to semantic speech classification. Concretely, can (1…
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.…
IRCoder: Intermediate Representations Make Language Models Robust Multilingual Code Generators
Indraneil Paul, Goran Glavaš, Iryna Gurevych
Code understanding and generation have fast become some of the most popular applications of language models (LMs). Nonetheless, research on multilingual aspects of Code-LMs (i.e.,…
Vicinal Risk Minimization for Few-Shot Cross-lingual Transfer in Abusive Language Detection
Gretel Liz De la Peña Sarracén, Paolo Rosso, Robert Litschko +2
Cross-lingual transfer learning from high-resource to medium and low-resource languages has shown encouraging results. However, the scarcity of resources in target languages remain…
SQATIN: Supervised Instruction Tuning Meets Question Answering for Improved Dialogue NLU
Evgeniia Razumovskaia, Goran Glavaš, Anna Korhonen +1
Task-oriented dialogue (ToD) systems help users execute well-defined tasks across a variety of domains (e.g., or ), with their Nat…
To Translate or Not to Translate: A Systematic Investigation of Translation-Based Cross-Lingual Transfer to Low-Resource Languages
Benedikt Ebing, Goran Glavaš
Perfect machine translation (MT) would render cross-lingual transfer (XLT) by means of multilingual language models (mLMs) superfluous. Given, on the one hand, the large body of wo…
AdaSent: Efficient Domain-Adapted Sentence Embeddings for Few-Shot Classification
Yongxin Huang, Kexin Wang, Sourav Dutta +3
Recent work has found that few-shot sentence classification based on pre-trained Sentence Encoders (SEs) is efficient, robust, and effective. In this work, we investigate strategie…
NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation
Andreea Iana, Goran Glavaš, Heiko Paulheim
NewsRecLib is an open-source library based on Pytorch-Lightning and Hydra developed for training and evaluating neural news recommendation models. The foremost goals of NewsRecLib…
Probing Cross-Lingual Lexical Knowledge from Multilingual Sentence Encoders
Ivan Vulić, Goran Glavaš, Fangyu Liu +3
Pretrained multilingual language models (LMs) can be successfully transformed into multilingual sentence encoders (SEs; e.g., LaBSE, xMPNet) via additional fine-tuning or model dis…