Google Maps can now write captions for your photos using AI
Google is rolling out new features to make it easier for users to contribute local knowledge to Maps. Most notably, Gemini can now create captions when users are looking to share a photo or video about a place.
4 days left to save close to $500 on TechCrunch Disrupt 2026 passes
Four days left to save up to $482 on your TechCrunch Disrupt 2026 ticket. These low rates will disappear on April 10 at 11:59 p.m. PT. Register now.
The AI gold rush is pulling private wealth into riskier, earlier bets
On a recent episode of Equity, we talked to Arena Private Wealth to explore a growing trend: family offices bypassing VCs to gain direct exposure to AI startups, turning them from passive investors into active participants.
Agile Governance Approach for Generative Artificial Intelligence in China
Autoencoder-Based Parameter Estimation for Superposed Multi-Component Damped Sinusoidal Signals
arXiv:2604.03985v1 Announce Type: new Abstract: Damped sinusoidal oscillations are widely observed in many physical systems, and their analysis provides access to underlying physical properties. However, parameter estimation becomes difficult when the signal decays rapidly, multiple components are superposed, and observational...
Shorter, but Still Trustworthy? An Empirical Study of Chain-of-Thought Compression
arXiv:2604.04120v1 Announce Type: new Abstract: Long chain-of-thought (Long-CoT) reasoning models have motivated a growing body of work on compressing reasoning traces to reduce inference cost, yet existing evaluations focus almost exclusively on task accuracy and token savings. Trustworthiness properties, whether...
Rethinking Token Prediction: Tree-Structured Diffusion Language Model
arXiv:2604.03537v1 Announce Type: new Abstract: Discrete diffusion language models have emerged as a competitive alternative to auto-regressive language models, but training them efficiently under limited parameter and memory budgets remains challenging. Modern architectures are predominantly based on a full-vocabulary token...
CAGMamba: Context-Aware Gated Cross-Modal Mamba Network for Multimodal Sentiment Analysis
arXiv:2604.03650v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) requires effective modeling of cross-modal interactions and contextual dependencies while remaining computationally efficient. Existing fusion approaches predominantly rely on Transformer-based cross-modal attention, which incurs quadratic complexity with respect to sequence length...
ActionNex: A Virtual Outage Manager for Cloud
arXiv:2604.03512v1 Announce Type: new Abstract: Outage management in large-scale cloud operations remains heavily manual, requiring rapid triage, cross-team coordination, and experience-driven decisions under partial observability. We present \textbf{ActionNex}, a production-grade agentic system that supports end-to-end outage assistance, including real-time updates,...
BioAlchemy: Distilling Biological Literature into Reasoning-Ready Reinforcement Learning Training Data
arXiv:2604.03506v1 Announce Type: new Abstract: Despite the large corpus of biology training text, the impact of reasoning models on biological research generally lags behind math and coding. In this work, we show that biology questions from current large-scale reasoning datasets...
RL-Driven Sustainable Land-Use Allocation for the Lake Malawi Basin
arXiv:2604.03768v1 Announce Type: new Abstract: Unsustainable land-use practices in ecologically sensitive regions threaten biodiversity, water resources, and the livelihoods of millions. This paper presents a deep reinforcement learning (RL) framework for optimizing land-use allocation in the Lake Malawi Basin to...
MetaSAEs: Joint Training with a Decomposability Penalty Produces More Atomic Sparse Autoencoder Latents
arXiv:2604.03436v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are increasingly used for safety-relevant applications including alignment detection and model steering. These use cases require SAE latents to be as atomic as possible. Each latent should represent a single coherent concept...
Regime-Calibrated Demand Priors for Ride-Hailing Fleet Dispatch and Repositioning
arXiv:2604.03883v1 Announce Type: new Abstract: Effective ride-hailing dispatch requires anticipating demand patterns that vary substantially across time-of-day, day-of-week, season, and special events. We propose a regime-calibrated approach that (i) segments historical trip data into demand regimes, (ii) matches the current...
Rashomon Memory: Towards Argumentation-Driven Retrieval for Multi-Perspective Agent Memory
arXiv:2604.03588v1 Announce Type: new Abstract: AI agents operating over extended time horizons accumulate experiences that serve multiple concurrent goals, and must often maintain conflicting interpretations of the same events. A concession during a client negotiation encodes as a ``trust-building investment''...
Knowledge Packs: Zero-Token Knowledge Delivery via KV Cache Injection
arXiv:2604.03270v1 Announce Type: new Abstract: RAG wastes tokens. We propose Knowledge Packs: pre-computed KV caches that deliver the same knowledge at zero token cost. For causal transformers, the KV cache from a forward pass on text F is identical to...
A Bayesian Information-Theoretic Approach to Data Attribution
arXiv:2604.03858v1 Announce Type: new Abstract: Training Data Attribution (TDA) seeks to trace model predictions back to influential training examples, enhancing interpretability and safety. We formulate TDA as a Bayesian information-theoretic problem: subsets are scored by the information loss they induce...
BlazeFL: Fast and Deterministic Federated Learning Simulation
arXiv:2604.03606v1 Announce Type: new Abstract: Federated learning (FL) research increasingly relies on single-node simulations with hundreds or thousands of virtual clients, making both efficiency and reproducibility essential. Yet parallel client training often introduces nondeterminism through shared random state and scheduling...
CODE-GEN: A Human-in-the-Loop RAG-Based Agentic AI System for Multiple-Choice Question Generation
arXiv:2604.03926v1 Announce Type: new Abstract: We present CODE-GEN, a human-in-the-Loop, retrieval-augmented generation (RAG)-based agentic AI system for generating context-aligned multiple-choice questions to develop student code reasoning and comprehension abilities. CODE-GEN employs an agentic AI architecture in which a Generator agent...
Don't Blink: Evidence Collapse during Multimodal Reasoning
arXiv:2604.04207v1 Announce Type: new Abstract: Reasoning VLMs can become more accurate while progressively losing visual grounding as they think. This creates task-conditional danger zones where low-entropy predictions are confident but ungrounded, a failure mode text-only monitoring cannot detect. Evaluating three...
Decomposing Communication Gain and Delay Cost Under Cross-Timestep Delays in Cooperative Multi-Agent Reinforcement Learning
arXiv:2604.03785v1 Announce Type: new Abstract: Communication is essential for coordination in \emph{cooperative} multi-agent reinforcement learning under partial observability, yet \emph{cross-timestep} delays cause messages to arrive multiple timesteps after generation, inducing temporal misalignment and making information stale when consumed. We formalize...
Contextual Control without Memory Growth in a Context-Switching Task
arXiv:2604.03479v1 Announce Type: new Abstract: Context-dependent sequential decision making is commonly addressed either by providing context explicitly as an input or by increasing recurrent memory so that contextual information can be represented internally. We study a third alternative: realizing contextual...
Automated Attention Pattern Discovery at Scale in Large Language Models
arXiv:2604.03764v1 Announce Type: new Abstract: Large language models have found success by scaling up capabilities to work in general settings. The same can unfortunately not be said for interpretability methods. The current trend in mechanistic interpretability is to provide precise...
AI startup Rocket offers vibe McKinsey-style reports at a fraction of the cost
Rocket's new AI platform combines strategy, product building, and competitive intelligence, aiming to move beyond code generation.
OpenAI alums have been quietly investing from a new, potentially $100M fund
Zero Shot, a new venture capital fund with deep ties to OpenAI, is aiming to raise $100 million for its first fund. It has already written some checks.
Google quietly launched an AI dictation app that works offline
Google's new offline-first dictation app uses Gemma AI models to take on the apps like Wispr Flow.
OpenAI’s vision for the AI economy: public wealth funds, robot taxes, and a four-day workweek
OpenAI proposes taxes on AI profits, public wealth funds, and expanded safety nets to address job loss and inequality, blending redistribution with capitalism as policymakers debate AI’s economic impact.
Spain’s Xoople raises $130 million Series B to map the Earth for AI
The company is also announcing a deal with L3Harris to build the sensors for Xoople's spacecraft.
Unlocking Prompt Infilling Capability for Diffusion Language Models
arXiv:2604.03677v1 Announce Type: new Abstract: Masked diffusion language models (dLMs) generate text through bidirectional denoising, yet this capability remains locked for infilling prompts. This limitation is an artifact of the current supervised finetuning (SFT) convention of applying response-only masking. To...
Adversarial Robustness of Deep State Space Models for Forecasting
arXiv:2604.03427v1 Announce Type: new Abstract: State-space model (SSM) for time-series forecasting have demonstrated strong empirical performance on benchmark datasets, yet their robustness under adversarial perturbations is poorly understood. We address this gap through a control-theoretic lens, focusing on the recently...