84 papers
FedPref: Federated Preference Learning for Structured Radiology Report Extraction
Flint Xiaofeng Fan, Cheston Tan, Yew-Soon Ong +1
Radiology reports describe findings and locations in free text, but downstream search and analysis require these relations in a fixed schema. Learning this extraction requires labe…
BitLogic: Training Framework for Gradient-Based FPGA-Native Neural Networks
Simon Bührer, Andreas Plesner, Aczel Till +1
Gradient-based LUT- and logic-gate-based neural networks (LUTNet, LogicNets, DiffLogic, PolyLUT, NeuraLUT, WARP-LUT, DWN, LILogicNet, LightLUT) replace multiply-accumulate arithmet…
Subcubic Coin Tossing in Asynchrony without PKI
Mose Mizrahi, Roger Wattenhofer
We consider an asynchronous network of parties connected to each other via secure channels, up to of which are byzantine. We study common coin tossing, a task where the par…
Post-Training Speech Enhancement Language Models with Perceptual Rewards
Frédéric Berdoz, Luca A. Lanzendörfer, Antonis Asonitis +1
Speech enhancement language models achieve strong results when trained on discrete audio tokens, but their optimization relies on token-level cross-entropy rather than the perceptu…
From Few to Many Faults: Optimal Adaptive Byzantine Agreement
Andrei Constantinescu, Marc Dufay, Anton Paramonov +1
Achieving agreement among distributed parties is a fundamental task in modern systems, underpinning applications such as consensus in blockchains, coordination in cloud infrastruct…
Data Attribution in Large Language Models via Bidirectional Gradient Optimization
Frédéric Berdoz, Luca A. Lanzendörfer, Kaan Bayraktar +1
Large Language Models (LLMs) are increasingly deployed across diverse applications, raising critical questions for governance, accountability, and data provenance. Understanding wh…