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Roni Itkin, Noam Issachar, Yehonatan Keypur, Yehonatan Keypur, Anpei Chen, Sagie Benaim

DR^{3}-Eval: Towards Realistic and Reproducible Deep Research Evaluation

DR^3-Eval is a new benchmark for evaluating deep research agents on complex multi-step tasks using a static corpus that simulates web complexity while remaining reproducible. It introduces a five-dimensional evaluation framework (Information Recall, Factual Accuracy, Citation Coverage, Instruction Following, Depth Quality) and reveals critical failure modes in retrieval robustness and hallucination control.See more

4dRoni Itkin, Noam Issachar, Yehonatan Keypur, Yehonatan Keypur, Anpei Chen, Sagie Benaim
R
Roni Itkin, Noam Issachar, Yehonatan Keypur, Yehonatan Keypur, Anpei Chen, Sagie Benaim

RAD-2: Scaling Reinforcement Learning in a Generator-Discriminator Framework

RAD-2 combines diffusion-based trajectory generation with RL-optimized reranking for autonomous driving motion planning. The framework achieves 56% collision rate reduction through temporal consistency in policy optimization and structured feedback mechanisms. Real-world deployment validates improved safety and smoothness in urban traffic scenarios.See more

4dRoni Itkin, Noam Issachar, Yehonatan Keypur, Yehonatan Keypur, Anpei Chen, Sagie Benaim
R
Roni Itkin, Noam Issachar, Yehonatan Keypur, Yehonatan Keypur, Anpei Chen, Sagie Benaim

GlobalSplat: Efficient Feed-Forward 3D Gaussian Splatting via Global Scene Tokens

GlobalSplat introduces a novel 3D Gaussian Splatting framework that reconstructs scenes using global scene tokens instead of pixel-aligned primitives, achieving competitive rendering with only 16K Gaussians (4MB footprint) and 78ms inference. The approach avoids representation bloat via coarse-to-fine training and global scene awareness. Benchmarked on RealEstate10K and ACID, it is significantly faster and more memory-efficient than dense baselines.See more

4dRoni Itkin, Noam Issachar, Yehonatan Keypur, Yehonatan Keypur, Anpei Chen, Sagie Benaim
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