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Repro - RoCA: Robust Cross-Domain End-to-End Autonomous Driving
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João Pedro Veiga
VeigaPunk
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AI & ML interests
Push boundaries
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Repro: Towards Efficient LLMs Annealing with Principled Sample Selection
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Repro: Optimizing Rank for High-Fidelity Implicit Neural Representations
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Repro: PipeSD: An Efficient Cloud-Edge Collaborative Pipeline Inference Framework with Speculative Decoding
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Repro: RelayCaching: Accelerating LLM Collaboration via Decoding KV Cache Reuse
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Repro: Rare Event Analysis of Large Language Models
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Repro: Enhancing Reasoning for Diffusion LLMs via Distribution Matching Policy Optimization
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Repro: Protein Autoregressive Modeling via Multiscale Structure Generation
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Repro: Steer Like the LLM: Activation Steering that Mimics Prompting
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Repro - Tokenised Flow Matching for Hierarchical Simulation Based Inference
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Repro - FAB: A First-Order AB-based Gradient Algorithm for Distributed Bilevel Optimization over T
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Repro - Heavy-Tailed Stochastic Gradients Q15yX0AZdr
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Repro - On the Interaction of Batch Noise, Adaptivity, and Compression, under $(L_0,L_1)$-Smoothne
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Repro - Delayed Momentum Aggregation: Communication-efficient Byzantine-robust Federated Learning
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Repro - Failure-Driven Workflow Refinement
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Repro - Discrete Adjoint Schrödinger Bridge Sampler
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Repro: To Grok Grokking — Provable Grokking in Ridge Regression
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Repro - MoSSP: A Momentum-Based Single-Loop Stochastic Penalty Method for Nonconvex Constrained DC
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Repro - Meta-Black-Box Optimization Can Do Search Guidance for Expensive Constrained Multi-Objecti
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Repro - To Grok Grokking: Provable Grokking in Ridge Regression
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