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An open-source, local, read-only MCP server that checks your request before Google quietly hands back nothing Ask the Google Search Console API for clicks filtered by country us and you get zero rows. No error, no warning, just nothing. It's not the only one.
Position: Stop Reactively Patching Your Model Every Time and Start Proactive Test-Driven AI Development Many modern AI systems are designed to operate under diverse, open-ended, use-cases.
Yujui Lin yujuil Thu, 10/01/2026 - 14:58 Research Area(s) Circuits and VLSI Design
Valentin Duruisseaux vduruisseaux Thu, 10/01/2026 - 14:34 Research Area(s) Artificial Intelligence and Machine Learning
Seul Lee Seull Thu, 10/01/2026 - 14:15 Research Area(s) Generative AI
Gongfan Fang gongfanf Thu, 10/01/2026 - 14:01 Research Area(s) Artificial Intelligence and Machine Learning Generative AI Natural Language Processing Main Field of Interest Artificial Intelligence and Machine Learning Google Scholar https://scholar.google.com/citations?user=489YZ_kAAAAJ&hl=en
Mid-Harness: Scaling Actions Between Model and Harness for Terminal Agents Terminal agents act through stochastic model generations, yet the ability to generate a useful action does not ensure its reliable execution.
Sihao Liu sihaol Wed, 09/30/2026 - 16:03 Sihao Liu is a Research Scientist in the Architecture Research Group at NVIDIA Research. His work spans computer architecture, programmable accelerators, and AI-assisted chip design.
Human2Any: Human-to-Robot Transfer via Constraint-Aware Compositional Planning cgarrett Tue, 09/15/2026 - 21:41
ShareMMU: Supporting Secure Address Translation Sharing among Untrusted Accelerators The growing demand for accelerated computing is driving widespread deployment of multi-accelerator systems in the cloud and at the edge.
FastGen-PDD: Parallel Decoding Distillation for Image and Video Generation Generation in video diffusion or flow models is computationally expensive due to the slow and iterative sampling process.
Composing Detector Error Models Fault-tolerant quantum programs thread together reusable logical operations, yet correcting errors requires comparing measurements across operation boundaries. Correlations tie each operation's error analysis to the computation around it.
ReasAlign: Reasoning Enhanced Safety Alignment against Prompt Injection Attack Large Language Models (LLMs) have enabled the development of powerful agentic systems capable of automating complex workflows across various fields.
ReasoningBomb: A Stealthy Denial-of-Service Attack by Inducing Pathologically Long Reasoning in Large Reasoning Models Large reasoning models (LRMs) extend large language models with explicit multi-step reasoning traces, but this capability introduces a new class of prompt-induced inference-time…
Architecting Secure AI Agents: Perspectives on System-Level Defenses Against Indirect Prompt Injection Attacks AI agents, predominantly powered by large language models (LLMs), are vulnerable to indirect prompt injection, in which malicious instructions embedded in untrusted data can trigger…
Learning to Track Instances without Video Annotations Tracking segmentation masks of multiple instances has been intensively studied, but still faces two fundamental challenges: 1) the requirement of large-scale, frame-wise annotation, and 2) the complexity of two-stage approaches.
Weakly-Supervised Physically Unconstrained Gaze Estimation A major challenge for physically unconstrained gaze estimation is acquiring training data with 3D gaze annotations for in-the-wild and outdoor scenarios.
Contrastive Syn-to-Real Generalization Training on synthetic data can be beneficial for label or data-scarce scenarios. However, synthetically trained models often suffer from poor generalization in real domains due to domain gaps.
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