62 citations · 146 across the 49 of their papers we have counts for
12 papers · 1 filter
Limited-Resource Adapters Are Regularizers, Not Linguists
Marcell Fekete, Nathaniel R. Robinson, Ernests Lavrinovics +4
Cross-lingual transfer from related high-resource languages is a well-established strategy to enhance low-resource language technologies. Prior work has shown that adapters show pr…
LAGO: Few-shot Crosslingual Embedding Inversion Attacks via Language Similarity-Aware Graph Optimization
Wenrui Yu, Yiyi Chen, Johannes Bjerva +2
We propose LAGO - Language Similarity-Aware Graph Optimization - a novel approach for few-shot cross-lingual embedding inversion attacks, addressing critical privacy vulnerabilitie…
Shared Path: Unraveling Memorization in Multilingual LLMs through Language Similarities
Xiaoyu Luo, Yiyi Chen, Johannes Bjerva +1
We present the first comprehensive study of Memorization in Multilingual Large Language Models (MLLMs), analyzing 95 languages using models across diverse model scales, architectur…
MultiHal: Multilingual Dataset for Knowledge-Graph Grounded Evaluation of LLM Hallucinations
Ernests Lavrinovics, Russa Biswas, Katja Hose +1
Large Language Models (LLMs) have inherent limitations of faithfulness and factuality, commonly referred to as hallucinations. Several benchmarks have been developed that provide a…
Follow the Path: Reasoning over Knowledge Graph Paths to Improve Large Language Model Factuality
Mike Zhang, Johannes Bjerva, Russa Biswas
We introduce fs1, a simple yet effective method that improves the factuality of reasoning traces by collecting them from large reasoning models and grounding them in knowledge grap…
NLP Security and Ethics, in the Wild
Heather Lent, Erick Galinkin, Yiyi Chen +3
As NLP models are used by a growing number of end-users, an area of increasing importance is NLP Security (NLPSec): assessing the vulnerability of models to malicious attacks and d…
On-Device LLMs for Home Assistant: Dual Role in Intent Detection and Response Generation
Rune Birkmose, Nathan Mørkeberg Reece, Esben Hofstedt Norvin +2
This paper investigates whether Large Language Models (LLMs), fine-tuned on synthetic but domain-representative data, can perform the twofold task of (i) slot and intent detection…
Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond
Qiongxiu Li, Xiaoyu Luo, Yiyi Chen +1
The role of memorization in machine learning (ML) has garnered significant attention, particularly as modern models are empirically observed to memorize fragments of training data.…
How Do Hackathons Foster Creativity? Towards AI Collaborative Evaluation of Creativity at Scale
Jeanette Falk, Yiyi Chen, Janet Rafner +3
Hackathons have become popular collaborative events for accelerating the development of creative ideas and prototypes. There are several case studies showcasing creative outcomes a…
ALGEN: Few-shot Inversion Attacks on Textual Embeddings using Alignment and Generation
Yiyi Chen, Qiongkai Xu, Johannes Bjerva
With the growing popularity of Large Language Models (LLMs) and vector databases, private textual data is increasingly processed and stored as numerical embeddings. However, recent…
HiFi-KPI: A Dataset for Hierarchical KPI Extraction from Earnings Filings
Rasmus T. Aavang, Giovanni Rizzi, Rasmus Tjalk-Bøggild +3
Accurate tagging of earnings reports can yield significant short-term returns for stakeholders. The machine-readable inline eXtensible Business Reporting Language (iXBRL) is mandat…
SEFL: A Framework for Generating Synthetic Educational Assignment Feedback with LLM Agents
Mike Zhang, Amalie Pernille Dilling, Léon Gondelman +3
Providing high-quality feedback on student assignments is crucial for student success, but it is heavily limited by time and budgetary constraints. In this work, we introduce Synth…