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Quantitative information flow (QIF) is concerned with measuring how much of a secret is leaked to an adversary who observes the result of a computation that uses it. Prior work has shown that QIF techniques based on abstract interpretation…

Programming Languages · Computer Science 2018-02-23 Ian Sweet , Jose Manuel Calderon Trilla , Chad Scherrer , Michael Hicks , Stephen Magill

The information bottleneck (IB) principle has been adopted to explain deep learning in terms of information compression and prediction, which are balanced by a trade-off hyperparameter. How to optimize the IB principle for better robustness…

Machine Learning · Computer Science 2021-03-04 Penglong Zhai , Shihua Zhang

Flip through any book or listen to any song lyrics, and you will come across pronouns that, in certain cases, can hinder meaning comprehension, especially for machines. As the role of having cognitive machines becomes pervasive in our…

Computation and Language · Computer Science 2023-08-30 Nicos Isaak

Adapting pretrained large language models (LLMs) to code domains via supervised fine-tuning (FT) has been commonly used for code generation. However, we identify a previously underappreciated failure mode, the memorization barrier, where…

Machine Learning · Computer Science 2025-10-21 Changsheng Wang , Xin Chen , Sijia Liu , Ke Ding

Quantitative information flow (QIF) is traditionally defined as the expected value of information leakage over all feasible program runs and it fails to identify vulnerable programs where only limited number of runs leak large amount of…

Cryptography and Security · Computer Science 2019-05-14 Bao Trung Chu , Kenji Hashimoto , Hiroyuki Seki

We present PitchFlower, a flow-based neural audio codec with explicit pitch controllability. Our approach enforces disentanglement through a simple perturbation: during training, F0 contours are flattened and randomly shifted, while the…

Audio and Speech Processing · Electrical Eng. & Systems 2025-10-30 Diego Torres , Axel Roebel , Nicolas Obin

As neural language models approach human performance on NLP benchmark tasks, their advances are widely seen as evidence of an increasingly complex understanding of syntax. This view rests upon a hypothesis that has not yet been empirically…

Computation and Language · Computer Science 2021-09-13 Nikolay Malkin , Sameera Lanka , Pranav Goel , Nebojsa Jojic

Disentanglement is a highly desirable property of representation owing to its similarity to human understanding and reasoning. Many works achieve disentanglement upon information bottlenecks (IB). Despite their elegant mathematical…

Machine Learning · Computer Science 2022-04-26 Jiantao Wu , Lin Wang , Bo Yang , Fanqi Li , Chunxiuzi Liu , Jin Zhou

Information flow analysis has largely ignored the setting where the analyst has neither control over nor a complete model of the analyzed system. We formalize such limited information flow analyses and study an instance of it: detecting the…

Cryptography and Security · Computer Science 2014-05-13 Michael Carl Tschantz , Amit Datta , Anupam Datta , Jeannette M. Wing

Early detection of developmental disorders can be aided by analyzing infant craniofacial morphology, but modeling infant faces is challenging due to limited data and frequent spontaneous expressions. We introduce BabyFlow, a generative AI…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Antonia Alomar , Mireia Masias , Marius George Linguraru , Federico M. Sukno , Gemma Piella

Emotional voice conversion (VC) aims to convert a neutral voice to an emotional (e.g. happy) one while retaining the linguistic information and speaker identity. We note that the decoupling of emotional features from other speech…

Audio and Speech Processing · Electrical Eng. & Systems 2021-10-05 Zhaojie Luo , Shoufeng Lin , Rui Liu , Jun Baba , Yuichiro Yoshikawa , Ishiguro Hiroshi

The information bottleneck principle is an elegant and useful approach to representation learning. In this paper, we investigate the problem of representation learning in the context of reinforcement learning using the information…

Machine Learning · Computer Science 2019-11-14 Pei Yingjun , Hou Xinwen

The fruits of science are relationships made comprehensible, often by way of approximation. While deep learning is an extremely powerful way to find relationships in data, its use in science has been hindered by the difficulty of…

Machine Learning · Computer Science 2022-04-18 Kieran A. Murphy , Dani S. Bassett

The two-pass information bottleneck (TPIB) based speaker diarization system operates independently on different conversational recordings. TPIB system does not consider previously learned speaker discriminative information while diarizing…

Audio and Speech Processing · Electrical Eng. & Systems 2020-10-14 Nauman Dawalatabad , Srikanth Madikeri , C Chandra Sekhar , Hema A Murthy

The muti-layer information bottleneck (IB) problem, where information is propagated (or successively refined) from layer to layer, is considered. Based on information forwarded by the preceding layer, each stage of the network is required…

Machine Learning · Statistics 2017-11-15 Qianqian Yang , Pablo Piantanida , Deniz Gündüz

To effectively study complex causal systems, it is often useful to construct abstractions of parts of the system by discarding irrelevant details while preserving key features. The Information Bottleneck (IB) method is a widely used…

Machine Learning · Computer Science 2025-06-12 Francisco N. F. Q. Simoes , Mehdi Dastani , Thijs van Ommen

We present a novel formal system for proving quantitative-leakage properties of programs. Based on a theory of Quantitative Information Flow (QIF) that models information leakage as a noisy communication channel, it uses "gain-functions"…

Logic in Computer Science · Computer Science 2025-06-17 Chris Chen , Annabelle McIver , Carroll Morgan

The information bottleneck problem (IB) of jointly stationary Gaussian sources is considered. A water-filling solution for the IB rate is given in terms of its SNR spectrum and whose rate is attained via frequency domain test-channel…

Information Theory · Computer Science 2022-08-23 Michael Dikshtein , Nir Weinberger , Shlomo Shamai

Text style transfer aims to alter the style of a sentence while preserving its content. Due to the lack of parallel corpora, most recent work focuses on unsupervised methods and often uses cycle construction to train models. Since cycle…

Computation and Language · Computer Science 2022-12-20 Kangchen Zhu , Zhiliang Tian , Ruifeng Luo , Xiaoguang Mao

In many complex systems, we observe that `interesting behaviour' is often the consequence of a system exploiting the existence of an Information Bottleneck (IB). These bottlenecks can occur at different scales, between individuals or…

Physics and Society · Physics 2023-08-02 Michael Crosscombe , Hiroki Sato