Capable but Careless: Do Computer-Use Agents Follow Contextual Integrity?
Paper • 2606.23189 • Published • 1
AI & ML interests
LLM, trustworthy AI, AI security, privacy, calibration, hallucination
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Privacy Collapse: Benign Fine-Tuning Can Break Contextual Privacy in Language Models
Is Multilingual LLM Watermarking Truly Multilingual? A Simple Back-Translation Solution
anmol
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haritzpuerto
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haritzpuerto
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ahmedheakl
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Planner and Executor: Collaboration between Discrete Diffusion And Autoregressive Models in Reasoning
Paper • 2510.15244 • Published
WorldCache: Content-Aware Caching for Accelerated Video World Models
Paper • 2603.22286 • Published • 5
Latent-DARM: Bridging Discrete Diffusion And Autoregressive Models For Reasoning
Paper • 2603.09184 • Published
MASEval: Extending Multi-Agent Evaluation from Models to Systems
Paper • 2603.08835 • Published
DocAtlas: Multilingual Document Understanding Across 80+ Languages
Paper • 2605.12623 • Published • 4
CEPO: RLVR Self-Distillation using Contrastive Evidence Policy Optimization
Paper • 2605.19436 • Published • 14
ahmedheakl
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cemde
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papers 3 months ago
Shh, don't say that! Domain Certification in LLMs
Paper • 2502.19320 • Published
Measuring what Matters: Construct Validity in Large Language Model Benchmarks
Paper • 2511.04703 • Published • 8
Privacy Collapse: Benign Fine-Tuning Can Break Contextual Privacy in Language Models
Paper • 2601.15220 • Published • 9
A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks
Paper • 2212.00720 • Published
haritzpuerto
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paper 4 months ago
ahmedheakl
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ahmedheakl
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mgubri
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