Towards Reliable Testing of Machine Unlearning
arXiv:2604.16536v1 Announce Type: new Abstract: Machine learning components are now central to AI-infused software systems, from recommendations and code assistants to clinical decision support. As re
Knowledge catalogue
arXiv:2604.16536v1 Announce Type: new Abstract: Machine learning components are now central to AI-infused software systems, from recommendations and code assistants to clinical decision support. As re
arXiv:2604.16579v1 Announce Type: new Abstract: Automated depression estimation is highly vulnerable to signal corruption and ambient noise in real-world deployment. Prevailing deterministic methods p
arXiv:2604.17089v1 Announce Type: new Abstract: Continual learning aims to update models under distribution shift without forgetting, yet many high-stakes deployments, such as healthcare, also require
arXiv:2602.09130v3 Announce Type: replace Abstract: Model compression is increasingly essential for deploying large language models (LLMs), yet existing comparative studies largely focus on pruning an
arXiv:2508.15815v3 Announce Type: replace Abstract: Modern large language models (LLMs) are typically trained and deployed using structured role tags (e.g. system, user, assistant, tool) that explicit
arXiv:2603.14975v2 Announce Type: replace-cross Abstract: Large Language Model agents deployed in complex environments frequently encounter a conflict between maximizing goal achievement and adhering
arXiv:2604.15789v1 Announce Type: new Abstract: As Large Language Models (LLMs) receive increasing attention and are being deployed across various domains, their potential risks, including generating
Boston Dynamics just gave its robot dog a brain that reasons about the physical world. Google DeepMind's Gemini Robotics model is now running inside Spot, the four-legged robot already deployed at tho
arXiv:2510.07043v2 Announce Type: replace Abstract: Human decision-making often involves constrained optimization. As LLM agents are deployed to assist with real-world tasks like travel planning, shop
arXiv:2510.03875v2 Announce Type: replace Abstract: The ability to solve motion-planning queries within a fixed time budget is critical for deploying robotic systems in time-sensitive applications. Se
arXiv:2507.16727v3 Announce Type: replace Abstract: Improving the reliability of large language models (LLMs) is critical for deploying them in real-world scenarios. In this paper, we propose extbf{De
arXiv:2604.15877v1 Announce Type: new Abstract: As LLM agents scale to long-horizon, multi-session deployments, efficiently managing accumulated experience becomes a critical bottleneck. Agent memory
Kimi wires up auth + database + backend in one pass One prompt gets you user registration, login, database, booking systems, admin dashboards - wired up and deployed. No separate 'now build the backen
arXiv:2604.15475v1 Announce Type: new Abstract: Deploying learned multi-robot models on heterogeneous robots remains challenging due to hardware heterogeneity, communication constraints, and the lack
arXiv:2604.15714v1 Announce Type: cross Abstract: Always-on converter health monitoring demands sub-mW edge inference, a regime inaccessible to GPU-based physics-informed neural networks. This work se
In this post, we'll show you how to build a complete omnichannel ordering system using Amazon Bedrock AgentCore, an agentic platform, to build, deploy, and operate highly effective AI agents securely
arXiv:2604.15937v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed to curate and rank human-created content, yet the nature and structure of their biases in these
arXiv:2604.15464v1 Announce Type: cross Abstract: Large Language Model (LLM) deployment is increasingly shifting to cost-efficient accelerators like Google's Tensor Processing Units (TPUs), prioritizi
arXiv:2604.15856v1 Announce Type: cross Abstract: Multimodal remote sensing data provide complementary information for semantic segmentation, but in real-world deployments, some modalities may be unav
arXiv:2604.15569v1 Announce Type: new Abstract: Manipulation policies deployed in uncontrolled real-world scenarios are faced with great in-category geometric diversity of everyday objects. In order t
arXiv:2603.19339v2 Announce Type: replace-cross Abstract: Dimensionality reduction is critical for deploying dense retrieval systems at scale, yet mainstream post-hoc methods face a fundamental trade-
Vercel, a major development platform that hosts and deploys web apps, was compromised, and the hackers are attempting to sell stolen data. A person claiming to be a member of ShinyHunters, which was b
arXiv:2604.14739v1 Announce Type: new Abstract: Large-scale renewable energy deployment introduces pronounced volatility into the electricity system, turning grid operation into a complex stochastic o
arXiv:2604.14602v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate toxic content, posing significant risks for safe deployment. Current mitigation strategies often degrad
arXiv:2604.14186v1 Announce Type: cross Abstract: Large self-supervised speech (SSL) models achieve strong downstream performance, but their size limits deployment in resource-constrained settings. We
Zo Computer achieved a 20-fold improvement in AI reliability by leveraging Vercel's infrastructure and deployment capabilities. The optimization likely involved implementing better error handling, red
Zscaler Inc.‘s new partnership with OpenAI Group PBC has the potential to transform the security firm’s cloud-native zero-trust platform into an engine that can both harden its own stack and help cust
arXiv:2604.14795v1 Announce Type: new Abstract: Visual Geometry Foundation Models (VGFMs) demonstrate remarkable zero-shot capabilities in local reconstruction. However, deploying them for kilometer-l
arXiv:2509.23638v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) models face memory and PCIe latency bottlenecks when deployed on commodity hardware. Offloading expert weights to CPU memor
arXiv:2602.03295v2 Announce Type: replace Abstract: Large Language Models (LLMs) and Vision-Language Models (VLMs) have demonstrated remarkable capabilities. However, their deployment is hindered by s
arXiv:2604.13474v1 Announce Type: cross Abstract: We propose a novel end-to-end privacy-preserving framework, instantiated by three efficient protocols for different deployment scenarios, covering bot
arXiv:2604.14629v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown remarkable capabilities in joint vision-language understanding, but their large scale poses significant challen
arXiv:2604.13417v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly deployed in mission-critical software systems, detecting hallucinations and ``faked truthfulness'' ha
arXiv:2604.14209v1 Announce Type: new Abstract: As deep neural networks are deployed in safety-critical domains such as autonomous driving and medical diagnosis, stakeholders need explanations that ar
Vercel Flags has reached general availability, enabling developers to implement feature flags and manage application behavior without requiring new deployments. This capability allows teams to control
arXiv:2604.13059v1 Announce Type: new Abstract: Most dialogue-based electronic medical record (EMR) systems still behave as passive pipelines: transcribe speech, extract information, and generate the
arXiv:2604.05672v3 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have emerged as a powerful paradigm for open-world robot manipulation, but their practical deployment is often c
arXiv:2604.13061v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in high-stakes autonomous and interactive workflows, where reliability demands continuous, multi-
arXiv:2604.13359v1 Announce Type: new Abstract: Biosignals exhibit substantial cross-subject and cross-session variability, inducing severe domain shifts that degrade post-deployment performance for s
💵⚠️ Blocking subagents are costing you 1) time: your supervisor is stuck waiting while they run, and 2) money: if they go off track you've burned tokens on work you can't course-correct. @huntlovell n
Databricks and Google Cloud have partnered to enable organizations to build and deploy data and AI solutions more efficiently. The collaboration integrates Databricks' lakehouse platform with Google C
arXiv:2604.13286v1 Announce Type: new Abstract: Despite the widespread multilingual deployment of large language models, post-training pipelines remain predominantly English-centric, contributing to p
arXiv:2604.13788v1 Announce Type: cross Abstract: Imitation learning (IL) policies in robotics deliver strong performance in controlled settings but remain brittle in real-world deployments: rare even
arXiv:2603.19790v3 Announce Type: replace Abstract: Modern vision-language models (VLMs) can act as generative OCR engines, yet open-ended decoding can expose rare but consequential failures. We ident
arXiv:2604.13466v1 Announce Type: cross Abstract: The Claude Mythos Preview system card deploys emotion vectors, sparse autoencoder (SAE) features, and activation verbalisers to study model internals
arXiv:2604.13803v1 Announce Type: new Abstract: Vision-language models are increasingly deployed in high-stakes settings, yet their susceptibility to sycophantic manipulation remains poorly understood
arXiv:2604.13248v1 Announce Type: new Abstract: Remote medical response systems are increasingly being deployed to support emergency care in disaster-affected and infrastructure-limited environments.
arXiv:2604.13981v1 Announce Type: new Abstract: Interpretability is essential for deploying object detection systems in critical applications, especially under low-quality imaging conditions that degr
arXiv:2604.14140v1 Announce Type: new Abstract: As language models are increasingly deployed for complex autonomous tasks, their ability to reason accurately over longer horizons becomes critical. An
Lua Global Inc. today announced it raised 5.8 million in early-stage funding to build a platform that allows any team, irrespective of its technical depth, to build, deploy and manage an agentic artif
Qwen3.6 is a model available through Ollama's model library, representing Alibaba's Qwen series of large language models optimized for local deployment. The model can be accessed and run through the O
NEW Research from Google. Integration test failures are painful because the signal is buried in messy logs. Massive output, heterogeneous systems, low signal-to-noise ratio, and unclear root causes. T
arXiv:2602.19315v2 Announce Type: replace Abstract: Underwater glider robots have become indispensable for ocean sampling, yet fully autonomous long-term operation remains rare in practice. Although s
arXiv:2603.28942v3 Announce Type: replace Abstract: The pervasive deployment of deep learning models across critical domains has concurrently intensified privacy concerns due to their inherent propens
arXiv:2604.13806v1 Announce Type: new Abstract: Large Language Models (LLMs) are widely used across many domains, but their scale makes deployment challenging. Post-Training Quantization (PTQ) reduces
We're proud to be on the @Forbes AI 50 list again! It reflects our focus on building secure, sovereign AI that helps enterprises and governments put their data to work on their terms. Learn more: http
arXiv:2603.10652v2 Announce Type: replace-cross Abstract: In real-world deployment, vision-language models often encounter disturbances such as weather, occlusion, and camera motion. Under such condit
Mistral AI has launched its Connectors API into Public Preview, enabling developers to register Model Context Protocol (MCP) connectors once and deploy them across multiple Mistral products. This 'bui
Modal's blog post covers how to build and deploy AI agent applications by combining Modal's serverless cloud infrastructure with OpenAI's Agent SDK, enabling scalable execution of agentic workflows. T
arXiv:2604.12491v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed for tabular question answering, yet calibration on structured data is largely unstudied. This pap