Tootfinder

Phase Transitions of the Additive Uniform Noise Channel with Peak Amplitude and Cost Constraint
Jonas Stapmanns, Catarina Dias, Luke Eilers, Tobias K\"uhn, Jean-Pascal Pfister
https://arxiv.org/abs/2510.12427

Phase Transitions of the Additive Uniform Noise Channel with Peak Amplitude and Cost Constraint
Under which condition is quantization optimal? We address this question in the context of the additive uniform noise channel under peak amplitude and cost constraints. We compute analytically the capacity-achieving input distribution as a function of the noise level, the average cost constraint, and the curvature of the cost function. We find that when the cost function is concave, the capacity-achieving input distribution is discrete, whereas when the cost function is convex and the cost const…

CoDA: Agentic Systems for Collaborative Data Visualization
Zichen Chen, Jiefeng Chen, Sercan \"O. Arik, Misha Sra, Tomas Pfister, Jinsung Yoon
https://arxiv.org/abs/2510.03194

CoDA: Agentic Systems for Collaborative Data Visualization
Deep research has revolutionized data analysis, yet data scientists still devote substantial time to manually crafting visualizations, highlighting the need for robust automation from natural language queries. However, current systems struggle with complex datasets containing multiple files and iterative refinement. Existing approaches, including simple single- or multi-agent systems, often oversimplify the task, focusing on initial query parsing while failing to robustly manage data complexity…

VeriGuard: Enhancing LLM Agent Safety via Verified Code Generation
Lesly Miculicich, Mihir Parmar, Hamid Palangi, Krishnamurthy Dj Dvijotham, Mirko Montanari, Tomas Pfister, Long T. Le
https://arxiv.org/abs/2510.05156

VeriGuard: Enhancing LLM Agent Safety via Verified Code Generation
The deployment of autonomous AI agents in sensitive domains, such as healthcare, introduces critical risks to safety, security, and privacy. These agents may deviate from user objectives, violate data handling policies, or be compromised by adversarial attacks. Mitigating these dangers necessitates a mechanism to formally guarantee that an agent's actions adhere to predefined safety constraints, a challenge that existing systems do not fully address. We introduce VeriGuard, a novel framework th…

Crosslisted article(s) found for cs.CR. https://arxiv.org/list/cs.CR/new
[1/1]:
- VeriGuard: Enhancing LLM Agent Safety via Verified Code Generation
Miculicich, Parmar, Palangi, Dvijotham, Montanari, Pfister, Le

EuroSpeech: A Multilingual Speech Corpus
Samuel Pfisterer, Florian Gr\"otschla, Luca A. Lanzend\"orfer, Florian Yan, Roger Wattenhofer
https://arxiv.org/abs/2510.00514

EuroSpeech: A Multilingual Speech Corpus
Recent progress in speech processing has highlighted that high-quality performance across languages requires substantial training data for each individual language. While existing multilingual datasets cover many languages, they often contain insufficient data for most languages. Thus, trained models perform poorly on the majority of the supported languages. Our work addresses this challenge by introducing a scalable pipeline for constructing speech datasets from parliamentary recordings. The p…

A Study of Neural Polar Decoders for Communication
Rom Hirsch, Ziv Aharoni, Henry D. Pfister, Haim H. Permuter
https://arxiv.org/abs/2510.03069 https://arx…

A Study of Neural Polar Decoders for Communication
In this paper, we adapt and analyze Neural Polar Decoders (NPDs) for end-to-end communication systems. While prior work demonstrated the effectiveness of NPDs on synthetic channels, this study extends the NPD to real-world communication systems. The NPD was adapted to complete OFDM and single-carrier communication systems. To satisfy practical system requirements, the NPD is extended to support any code length via rate matching, higher-order modulations, and robustness across diverse channel co…

Crosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[3/11]:
- HEART: Emotionally-driven test-time scaling of Language Models
Pinto, Goyal, Song, Chakraborty, Wang, Pfister, Palangi

Crosslisted article(s) found for cs.IR. https://arxiv.org/list/cs.IR/new
[1/1]:
- LLM-based Multi-Agent Blackboard System for Information Discovery in Data Science
Salemi, Parmar, Goyal, Song, Yoon, Zamani, Palangi, Pfister

The multivariate Herglotz-Nevanlinna class: Rational approximation
Mainak Bhowmik, Mihai Putinar
https://arxiv.org/abs/2509.15668 https://arxiv.org/pdf/250…

The multivariate Herglotz-Nevanlinna class: Rational approximation
We return to Takagi's variational principle, generalized after forty years to two complex variables by Pfister. Both isolating some extremal rational functions associated to a bounded holomorphic function in the unit disk, respectively the bidisk. The rational inner functions arising from the Takagi-Pfister skew eigenvectors lead to a Pade type approximation scheme. For these rational functions, we prove a Montessus de Ballore type convergence theorem, on the polydisk in any complex dimension. …

DS-STAR: Data Science Agent via Iterative Planning and Verification
Jaehyun Nam, Jinsung Yoon, Jiefeng Chen, Jinwoo Shin, Tomas Pfister
https://arxiv.org/abs/2509.21825 https://…

DS-STAR: Data Science Agent via Iterative Planning and Verification
Data science, which transforms raw data into actionable insights, is critical for data-driven decision-making. However, these tasks are often complex, involving steps for exploring multiple data sources and synthesizing findings to deliver insightful answers. While large language models (LLMs) show significant promise in automating this process, they often struggle with heterogeneous data formats and generate sub-optimal analysis plans, as verifying plan sufficiency is inherently difficult with…