AI News Archive: April 28, 2026 — Part 25
Sourced from 500+ daily AI sources, scored by relevance.
- Using Large Language Models for Black-Box Testing of FMU-Based Simulations
We propose a human in the loop approach for black-box testing of Functional Mock-up Units (FMUs) using Large Language Models (LLMs). The goal is to reduce the manual effort in defining test scenarios for dynamic simulation models and to improve the interpretability of results. The approach takes the...
- CoRE: A Fine-Grained Code Reasoning Benchmark Beyond Output Prediction
Despite strong performance on code generation tasks, it remains unclear whether large language models (LLMs) genuinely reason about code execution. Existing code reasoning benchmarks primarily evaluate final output correctness under a single canonical implementation, leaving two critical aspects und...
- AI as Consumer and Participant: A Co-Design Agenda for MBSE Substrates and Methodology
AI tools are being deployed over MBSE models today, and those models were not designed for this kind of consumption. The problem is not simply that tools hallucinate: well-prompted frontier models produce competent, useful output over a conformant SysML model, but the reasoning they produce is drawn...
- DiRe-RAPIDS: Topology-faithful dimensionality reduction at scale
Dimensionality reduction methods such as UMAP and t-SNE are central tools for visualising high-dimensional data, but their local-neighborhood objectives can preserve sampling noise while distorting global topology. We show that standard local metrics reward this noise memorisation: top-performing em...
- ML-SAN: Multi-Level Speaker-Adaptive Network for Emotion Recognition in Conversations
To establish empathy with machines, it is essential to fully understand human emotional changes. However, research in multimodal emotion recognition often overlooks one problem: individual expressive traits vary significantly, which means that different people may express emotions differently. In ou...
- UNet-Based Fusion and Exponential Moving Average Adaptation for Noise-Robust Speaker Recognition
The joint training of speech enhancement and speaker embedding networks for speaker recognition is widely adopted under noisy acoustic environments. While effective, this paradigm often fails to leverage the generalization and robustness benefits inherent in large-scale speech enhancement pre-traini...
- K-CARE: Knowledge-driven Symmetrical Contextual Anchoring and Analogical Prototype Reasoning for E-commerce Relevance
This paper targets e-commerce search relevance. While Large Language Models (LLMs) have demonstrated significant potential in this field, they often encounter performance bottlenecks in persistent 'corner cases' within complex industrial scenarios. Existing research primarily focuses on optimizing r...
- Make Any Collection Navigable: Methods for Constructing and Evaluating Hypergraph of Text
One reason the Web is more useful than a simple collection of documents is that the structure created by hyperlinks enables flexible navigation from one web page to another. However, hyperlinks are typically created manually and cannot fully capture a corpus' implicit semantic structures. Is there a...
- Break the Inaccessible Boundary: Distilling Post-Conversion Content for User Retention Modeling
User retention is a key metric to measure long-term engagement in modern platforms. In real-time bidding (RTB) advertising system for user re-engagement, the retention model is required to predict future revisit probability at bidding time, before the user converts and consumes any content. Although...
- Harmonizing Generative Retrieval and Ranking in Chain-of-Recommendation
Generative recommender systems have recently emerged as a promising paradigm by formulating next-item prediction as an auto-regressive semantic IDs generation, such as OneRec series works. However, with the next-item-agnostic prediction paradigm, its could beam out some next potential items via Sema...
- Personalized Multi-Interest Modeling for Cross-Domain Recommendation to Cold-Start Users
Cross-domain recommendation (CDR) has demonstrated to be an effective solution for alleviating the user cold-start issue. By leveraging rich user-item interactions available in a richly informative source domain, CDR could improve the recommendation performance for cold-start users in the target dom...
- From Citation Selection to Citation Absorption: A Measurement Framework for Generative Engine Optimization Across AI Search Platforms
Generative search engines increasingly determine whether online information is merely discoverable, cited as a source, or actually absorbed into generated answers. This paper proposes a two-stage measurement framework for Generative Engine Optimization (GEO): citation selection, where a platform tri...
- The Attention Market: Interpreting Online Fair Re-ranking as Manifold Optimization under Walrasian Equilibrium
Fair re-ranking aims to promote long-tail items and enhance diversity within groups in information retrieval. While previous research on online fairness-aware re-ranking has shown promising outcomes, our comprehensive evaluation of online fair re-ranking methods over 20 settings reveals significant ...
- From Local Indices to Global Identifiers: Generative Reranking for Recommender Systems via Global Action Space
In modern recommender systems, list-wise reranking serves as a critical phase within the multi-stage pipeline, finalizing the exposed item sequence and directly impacting user satisfaction by modeling complex intra-list item dependencies. Existing methods typically formulate this task as selecting i...
- UnIte: Uncertainty-based Iterative Document Sampling for Domain Adaptation in Information Retrieval
Unsupervised domain adaptation generalizes neural retrievers to an unseen domain by generating pseudo queries on target domain documents. The quality and efficiency of this adaptation critically depend on which documents are selected for pseudo query generation. The existing document sampling method...
- Improving Biological Sequence Prediction with AlphaFold2 Representation
Motivation: Accurate prediction of functional sites from primary sequences is essential for elucidating biological mechanisms and advancing rational drug design. However, traditional sequence-based features areinherently unable to capture complex structural protein contexts. Recently, AlphaFold2 (AF2) revolutionized protein structure prediction, raising expectations of AF2 to serve as a feature extractor providing structure- rich representation, which can be useful for sequence-based prediction, particularly for unknown sequences. Results: We present a novel feature-engineering paradigm that leverages a high-dimensional latent representation matrix (of L multiply D, where L is the sequence length and D is the feature dimension size) extracted directly from the AF2 Evoformer module. We systematically evaluated the AF2 representation, comparing with conventional sequence-based features, such as hidden Markov model profiles, using a variety of machine learning models, on two structurally
- Protein Function Prediction with Pretrained ProtT5 Embeddings and Gradient Boosting
Protein function prediction remains a central challenge in computational biology due to the extreme sparsity and long-tail distribution of Gene Ontology (GO) [1] annotations. Advances in protein language models enable the extraction of dense, fixed-length representations from amino acid sequences, offering a scalable alternative to hand-picked features such as physicochemical properties. In this work, we evaluate a transformer-based embedding approach using ProtT5-XL combined with classical and modern multi-label classifiers for Gene Ontology prediction in the CAFA-6 setting. Fixed-length embeddings were generated via mean pooling of transformer hidden states and used as input to one-vs-rest logistic regression, gradient-boosted decision trees, and a neural network. Models were evaluated on held-out validation data with a focus on threshold selection, prediction sparsity, and behavior across frequent and rare GO terms. Gradient boosting consistently provided the best balance between pr
- Passive acoustic monitoring as a tool for early detection of invasive animal species: a systematic review and a case study
Invasive animal species are spreading rapidly across the globe, creating an urgent need for efficient early-detection and monitoring tools. Passive acoustic monitoring has become an established method in biodiversity research, but its application to invasive species monitoring has been less systematically explored. Here, we combine a systematic literature review with a field-based case study to evaluate the potential of passive acoustic monitoring for invasive animal detection. We identified 26 studies on acoustic monitoring of invasive animals, mainly addressing amphibians (11 studies), birds and fish (five each) with most studies from the USA and Australia. The use of acoustic monitoring of invasive species has increased during the past decade, with recent studies applying automated detection, machine learning, and large-scale monitoring frameworks. As a case study, we further tested the feasibility of low-cost acoustic monitoring of the invasive American bullfrog (Lithobates catesbe
- Elon Musk takes stand in trial vs. Sam Altman that could reshape AI’s future
Elon Musk takes stand in trial vs. Sam Altman that could reshape AI’s future Boston Herald
- Elon Musk takes stand in trial vs. Sam Altman that could reshape AI's future
Elon Musk takes stand in trial vs. Sam Altman that could reshape AI's future
- UAE students build AI tools to predict heart attacks, prevent amputations
UAE students build AI tools to predict heart attacks, prevent amputations
- Aexa Aerospace® and SpacePort Australia® Work together to create the world’s first deductive medical AI
Aexa Aerospace® and SpacePort Australia® Work together to create the world’s first deductive medical AI The Arizona Republic
- Elon Musk takes stand in trial vs. Sam Altman that could reshape AI’s future
Elon Musk takes stand in trial vs. Sam Altman that could reshape AI’s future The Mercury News
- A Tiny Town Is Building So Many Data Centers That There’ll Be Almost Nothing Else Left
“THE PUBLIC TRUST HAS BEEN VIOLATED." The post A Tiny Town Is Building So Many Data Centers That There’ll Be Almost Nothing Else Left appeared first on Futurism .
- Musk and Altman show up for trial that could reshape AI
The bickering billionaires' early-morning appearances foreshadow what could be a dramatic start to a legal drama that is expected to be brimming with intrigue and potentially embarrassing details about the two tech moguls.
- Google Gemini Proactive Assistance Handles Tasks Before You Ask for Them
Google Gemini Proactive Assistance Handles Tasks Before You Ask for Them PCMag Australia
- Here’s your first look at Google’s upcoming ‘Proactive Assistance’ feature for Gemini
The new feature will make Gemini better at anticipating your needs and provide help even before you ask for it.
- Elon Musk takes stand in trial vs. Sam Altman that could reshape AI's future
Elon Musk takes stand in trial vs. Sam Altman that could reshape AI's future Inquirer.com
- AWS accelerates enterprise agentic automation with expanded Amazon Connect portfolio
Amazon Web Services Inc. is moving agentic artificial intelligence up the software stack with the launch today of an expanded Amazon Connect portfolio, which has evolved into four distinct offerings that aim to automate complex, industry-specific workflows. The expansion effectively rebrands the original Amazon Connect cloud contact center service into Amazon Connect Customer AI, while […] The post AWS accelerates enterprise agentic automation with expanded Amazon Connect portfolio appeared first on SiliconANGLE .
- SAS expands agentic AI and governance capabilities with broad platform updates
SAS Institute Inc. is using its SAS Innovate conference this week to introduce a sweeping set of product updates aimed at helping enterprises operationalize artificial intelligence with stronger governance, integrated data management and expanded agentic AI capabilities. The announcements center on a new governance layer, enhancements to the SAS Viya platform and a growing portfolio […] The post SAS expands agentic AI and governance capabilities with broad platform updates appeared first on SiliconANGLE .
- Kaseya shifts from AI ‘insights’ to autonomous action with new agentic platform
Kaseya shifts from AI ‘insights’ to autonomous action with new agentic platform IT Pro
- Startup Lovelace targets contextual AI engine at mission-critical use cases
Lovelace AI Inc. is emerging from stealth mode today with an approach to enterprise artificial intelligence that it says is necessary for high-stakes decision-making, particularly in environments where errors can have significant consequences. At the core of the company’s approach is a “context engine” builder called Elemental that’s designed to sit between AI agents and […] The post Startup Lovelace targets contextual AI engine at mission-critical use cases appeared first on SiliconANGLE .
- Why all eyes are on AI spending at Microsoft and Amazon
Amazon and Microsoft report earnings at the same time on Wednesday. What does Wall Street want to see?
- Elon Musk takes stand in trial vs. Sam Altman that could reshape AI’s future
Elon Musk takes stand in trial vs. Sam Altman that could reshape AI’s future The Denver Post
- Amazon Earnings Preview: AI Momentum In Focus, But This Number Could Be 'Messy'
Amazon stock is picking up strength as the tech giant prepares to report its first-quarter results late Wednesday. The post Amazon Earnings Preview: AI Momentum In Focus, But This Number Could Be 'Messy' appeared first on Investor's Business Daily .
- Elon Musk takes stand in trial vs. Sam Altman that could reshape AI’s future
Elon Musk, the Tesla CEO, world’s richest man and OpenAI’s cofounder, took the stand Tuesday in a high-stakes trial revolving around a bitter feud between himself and former friends Sam Altman and Greg Brockman that could reshape the future development of artificial intelligence.
- Facial recognition data is a key to your identity. If stolen, you can't just change the locks
A woman strolls into a grocery store, thinking about grabbing some apples. Before she even reaches the produce aisle, a security camera has scanned her face. Whether the system is checking for shoplifters or simply logging her arrival, her face has joined a digital ledger, a trace she can't easily erase. Retailers, banks, airports, stadiums and office buildings are doing the same.
- Lion to embed AI across its operations
Beverage maker partners with OpenAI.
- Beth Israel Lahey to roll out system-wide AI tool
The AI tool is meant to combat administrative burnout in doctors.
- Register: Risky Future AI Tools for Commercial Auto, Telematics & Fleet Risks on April 29
Insurance Journal’s Risky Future series is hosting the “Commercial Auto, Telematics & Fleet Risks” Demo Day, a series of free AI tool demonstrations designed exclusively for commercial auto carriers, fleet underwriters, risk managers, brokers and more. This event features vendors …
- Sharper AI eyes for maritime safety
Sharper AI eyes for maritime safety EurekAlert!
- Amazon touts a 'major expansion' with OpenAI as Microsoft ties loosen
Amazon announced what it called a "major expansion" of its partnership with ChatGPT maker OpenAI on Tuesday, a day after the artificial intelligence company said it was loosening its ties to longtime backer Microsoft.
- AdMarketplace Is Piloting Performance Ads In AI Chat
AI chat is starting to look more and more like a media channel, which means someone’s gotta figure out the ad model. Although chatbot conversations are loaded with commercial intent – ChatGPT knows it – there’s still no clear playbook for monetizing those interactions without messing with the user experience. Search advertising specialist adMarketplace is one of […] The post AdMarketplace Is Piloting Performance Ads In AI Chat appeared first on AdExchanger .
- You probably wouldn't notice if an AI chatbot slipped ads into its responses
Hundreds of millions of people consult artificial intelligence chatbots on a daily basis for everything from product recommendations to romance, making them a tempting audience to target with potentially below-the-radar advertising. Indeed, our research suggests AI chatbots could easily be used for covert advertising to manipulate their human users.
- Datavault AI (NASDAQ: DVLT) Secures $120M Term Sheet With Scilex for Quantum-Ready Edge Network Buildout
Datavault AI (NASDAQ: DVLT) Secures $120M Term Sheet With Scilex for Quantum-Ready Edge Network Buildout USA Today
- Amazon touts a ‘major expansion’ with OpenAI as Microsoft ties loosen
Amazon touts a ‘major expansion’ with OpenAI as Microsoft ties loosen Boston Herald
- Datavault AI Announces Execution of Binding Term Sheet for $120 Million Cash Contribution From Scilex Holding Company to Fund 100-City GPU Expansion of Quantum-Ready SanQtum Platform
Datavault AI Announces Execution of Binding Term Sheet for $120 Million Cash Contribution From Scilex Holding Company to Fund 100-City GPU Expansion of Quantum-Ready SanQtum Platform The Arizona Republic
- Amazon touts a 'major expansion' with OpenAI as Microsoft ties loosen
Amazon announced what it called a “major expansion” of its partnership with ChatGPT maker OpenAI on Tuesday, a day after the artificial intelligence company said it was loosening its ties to longtime backer Microsoft
- GOP-led Florida House plays hardball with DeSantis on AI, medical freedom — again
GOP-led Florida House plays hardball with DeSantis on AI, medical freedom — again Miami Herald
- Amazon touts a 'major expansion' with OpenAI as Microsoft ties loosen
Amazon touts a 'major expansion' with OpenAI as Microsoft ties loosen Houston Chronicle