15 citations · 35 across the 11 of their papers we have counts for
12 papers
GLM-RAG: Graph Language Models for Graph-Based Retrieval-Augmented Generation
Maya Arseven, Anette Frank, Beni Egressy +2
Retrieval-augmented generation (RAG) over knowledge graphs requires retrievers that can effectively capture both graph structure and semantic information. Recent approaches have ex…
Beyond Pairwise Correlations: Higher-Order Redundancies in Self-Supervised Representation Learning
David Zollikofer, Béni Egressy, Frederik Benzing +2
Several self-supervised learning (SSL) approaches have shown that redundancy reduction in the feature embedding space is an effective tool for representation learning. However, the…
Graph Dimension Attention Networks for Enterprise Credit Assessment
Shaopeng Wei, Beni Egressy, Xingyan Chen +4
Enterprise credit assessment is critical for evaluating financial risk, and Graph Neural Networks (GNNs), with their advanced capability to model inter-entity relationships, are a…
Graphtester: Exploring Theoretical Boundaries of GNNs on Graph Datasets
Eren Akbiyik, Florian Grötschla, Beni Egressy +1
Graph Neural Networks (GNNs) have emerged as a powerful tool for learning from graph-structured data. However, even state-of-the-art architectures have limitations on what structur…
Realistic Synthetic Financial Transactions for Anti-Money Laundering Models
Erik Altman, Jovan Blanuša, Luc von Niederhäusern +3
With the widespread digitization of finance and the increasing popularity of cryptocurrencies, the sophistication of fraud schemes devised by cybercriminals is growing. Money laund…
Provably Powerful Graph Neural Networks for Directed Multigraphs
Béni Egressy, Luc von Niederhäusern, Jovan Blanusa +3
This paper analyses a set of simple adaptations that transform standard message-passing Graph Neural Networks (GNN) into provably powerful directed multigraph neural networks. The…
Cascaded Beam Search: Plug-and-Play Terminology-Forcing For Neural Machine Translation
Frédéric Odermatt, Béni Egressy, Roger Wattenhofer
This paper presents a plug-and-play approach for translation with terminology constraints. Terminology constraints are an important aspect of many modern translation pipelines. In…
Graph Neural Networks with Precomputed Node Features
Beni Egressy, Roger Wattenhofer
Most Graph Neural Networks (GNNs) cannot distinguish some graphs or indeed some pairs of nodes within a graph. This makes it impossible to solve certain classification tasks. Howev…
A Plug-and-Play Method for Controlled Text Generation
Damian Pascual, Beni Egressy, Clara Meister +2
Large pre-trained language models have repeatedly shown their ability to produce fluent text. Yet even when starting from a prompt, generation can continue in many plausible direct…
Bailouts in Financial Networks
Beni Egressy, Roger Wattenhofer
We consider networks of banks with assets and liabilities. Some banks may be insolvent, and a central bank can decide which insolvent banks, if any, to bail out. We view bailouts a…
Directed Beam Search: Plug-and-Play Lexically Constrained Language Generation
Damian Pascual, Beni Egressy, Florian Bolli +1
Large pre-trained language models are capable of generating realistic text. However, controlling these models so that the generated text satisfies lexical constraints, i.e., contai…
Brain2Word: Decoding Brain Activity for Language Generation
Nicolas Affolter, Beni Egressy, Damian Pascual +1
Brain decoding, understood as the process of mapping brain activities to the stimuli that generated them, has been an active research area in the last years. In the case of languag…