6 papers
Sparks of Rationality: Do Reasoning LLMs Align with Human Judgment and Choice?
Ala N. Tak, Amin Banayeeanzade, Anahita Bolourani +5
Large Language Models (LLMs) are increasingly positioned as decision engines for hiring, healthcare, and economic judgment, yet real-world human judgment reflects a balance between…
On the Limits of Momentum in Decentralized and Federated Optimization
Riccardo Zaccone, Sai Praneeth Karimireddy, Carlo Masone
Recent works have explored the use of momentum in local methods to enhance distributed SGD. This is particularly appealing in Federated Learning (FL), where momentum intuitively ap…
DISCO: A Browser-Based Privacy-Preserving Framework for Distributed Collaborative Learning
Julien T. T. Vignoud, Valérian Rousset, Hugo El Guedj +28
Data is often impractical to share for a range of well considered reasons, such as concerns over privacy, intellectual property, and legal constraints. This not only fragments the…
Reject Only Critical Tokens: Pivot-Aware Speculative Decoding
Amir Ziashahabi, Yavuz Faruk Bakman, Duygu Nur Yaldiz +3
Speculative Decoding (SD) ensures that the output matches the target model's distribution exactly. However, we argue that this distribution matching requirement is too stringent an…
Uncertainty as Feature Gaps: Epistemic Uncertainty Quantification of LLMs in Contextual Question-Answering
Yavuz Bakman, Sungmin Kang, Zhiqi Huang +8
Uncertainty Quantification (UQ) research has primarily focused on closed-book factual question answering (QA), while contextual QA remains unexplored, despite its importance in rea…
TruthTorchLM: A Comprehensive Library for Predicting Truthfulness in LLM Outputs
Duygu Nur Yaldiz, Yavuz Faruk Bakman, Sungmin Kang +9
Generative Large Language Models (LLMs)inevitably produce untruthful responses. Accurately predicting the truthfulness of these outputs is critical, especially in high-stakes setti…