CS
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
Failing grades soar with AI usage, dwindling math skills in Berkeley CS classes
Article URL: https://www.dailycal.org/news/campus/academics/failing-grades-soar-as-professors-see-greater-ai-usage-dwindling-math-skills-in-uc-berkeley/article_16fad0bf-02cb-4b8c-8d88-888ffd9f8608.html Comments URL: https://news.ycombinator.com/item?id=48392004 Points: 30 # Comments: 11
Towards Truly Multilingual ASR: Generalizing Code-Switching ASR to Unseen Language Pairs
arXiv:2606.05846v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) has become a key technology for human--AI interaction. However, code-switching ASR (CS-ASR) remains particularly challenging due to the severe scarcity of multilingual CS speech resources across diverse language pairs. Existing approaches primarily improve CS-ASR performance through synthetic CS speech generation or pair-specific fine-tuning on limited bilingual datasets.
Beyond Single Solution: Multi-Hypothesis Collaborative Deep Unfolding Network for Image Compressive Sensing
arXiv:2606.03666v1 Announce Type: new Abstract: Recent deep unfolding networks (DUNs) have advanced Compressive Sensing (CS) by effectively integrating iterative optimization with deep learning architectures. However, most CS approaches predominantly confine their inference to a single solution space, neglecting the inherent ill-posedness of CS problems that intrinsically permits multiple plausible candidate hypotheses. In this paper, a novel Multi-Hypothesis Collaborative Deep Unfolding CS...
Contrastive Training with LLM-generated Near-Misses for Robust Code-Switching Speech Recognition
new Abstract: Code-switching (CS), the alternation between multiple languages within a single utterance, remains challenging for Automatic Speech Recognition (ASR). To address this issue, we propose a Point-of-Interest (POI)-aware contrastive training framework that improves recognition at CS-critical regions. We first identify CS spans by adopting POI detection method from literature, then construct acoustically plausible near-miss hypotheses by perturbing POIs in ASR N-best outputs and...
Improving the Efficiency and Effectiveness of LLM Knowledge Distillation for Conversational Search
arXiv:2606.04650v1 Announce Type: new Abstract: Conversational Search (CS) considers retrieval of relevant documents based on conversational context. Large Language Models (LLMs) have significantly enhanced CS by enabling effective query rewriting. However, employing LLMs during inference poses efficiency challenges.
An Energy-Stable Implicit Convex-Splitting BDF2 Scheme for the Cahn-Hilliard-Navier-Stokes Equations
Announce Type: new Abstract: We develop an energy-stable implicit convex-splitting BDF2 discretization (CS-BDF2) of the Cahn--Hilliard--Navier--Stokes equations. For the Cahn--Hilliard equation, BDF2 analyses can establish energy stability by testing the phase equation in the (H^{-1}) metric. For CHNS, this test is not compatible with the coupled energy estimate: the momentum equation is tested by (\bfu^{n+1}), while the transported phase equation is tested by (\mu^{n+1}) so that transport...
The screenless Camp Snap 2 is slimmer and comes with more filters
The new Camp Snap 2 is 15 percent slimmer than the original version. Camp Snap After expanding its offerings to video with the CS-8 inspired by Kodak and Canon's retro Super 8mm film cameras, Camp Snap is returning to its roots. The Camp Snap 2 is a sequel to the company's first screenless digital point-and-shoot camera that updates the original with a slimmer design, faster performance, filters available right out of the box, and new features making it easier for kids to use.
A Computational Toolkit for Engagement and Scalable Assessment in a Large Logic Course
Announce Type: new Abstract: Large required courses in theoretical computer science face two related challenges: helping students engage with abstract material and supporting reliable student assessment at scale. This paper describes LogicLab, a lightweight computational toolkit developed for CS 245, Logic and Computation, at the University of Waterloo.
Restartable Sequences
May 31st, 2026 @ justine's web page The best kept secret at the frontier of system programming right now is the Linux 4.18+ (c. 2018) concept of restartable sequences or rseq for short. They allow you to create thread-safe data structures without locks or atomics which scale to microprocessors with many cores. It's currently only possible to use rseq on Linux using handwritten assembly code.
Layerwise Terminal Discrepancy in Chen's Reverse-Heat Coupling on the Boolean Cube
arXiv:2606.04573v1 Announce Type: cross Abstract: We isolate a layerwise refinement of the terminal testing-discrepancy step in Chen's perturbed reverse-heat approach~\cite{Chen2026} to Talagrand's convolution conjecture on the Boolean cube. Built on the joint-filtration martingale formulation of Chen's coupling, and on Chen's approximate monotonicity and conditional squared-score estimates being available in the joint-filtration form stated below, we prove the localized testing estimate \[...