MongoDB - Build AI That Scales
Mini toolsPapers
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MegaScale-MoE: Large-Scale Communication-Efficient Training of Mixture-of-Experts Models in Production
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The $qs$ Inequality: Quantifying the Double Penalty of Mixture-of-Experts at Inference
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Dynamic Chunking Diffusion Transformer
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AI+HW 2035: Shaping the Next DecadeNVIDIA, Google, AMD, IBM, Together AI, OpenAI, SEMRON, EnCharge AI, SambaNova, SK Hynix, Oracle / Agentrys, Brown University, California Institute of Technology, Carnegie Mellon University, Hewlett Packard Labs, New York University, Princeton University, Stanford University, University at Buffalo, University of California, University of Illinois Urbana-Champaign, University of Pennsylvania, University of Texas
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Parallelization Strategies for Dense LLM Deployment: Navigating Through Application-Specific Tradeoffs and Bottlenecks
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GUI-GENESIS: Automated Synthesis of Efficient Environments with Verifiable Rewards for GUI Agent Post-Training
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GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning
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AdaptEvolve: Improving Efficiency of Evolutionary AI Agents through Adaptive Model Selection
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Canzona: A Unified, Asynchronous, and Load-Balanced Framework for Distributed Matrix-based Optimizers
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M2XFP: A Metadata-Augmented Microscaling Data Format for Efficient Low-bit Quantization
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Zebra-Llama: Towards Extremely Efficient Hybrid Models
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Power Aware Dynamic Reallocation For Inference
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AIE4ML: An End-to-End Framework for Compiling Neural Networks for the Next Generation of AMD AI Engines
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CD4LM: Consistency Distillation and aDaptive Decoding for Diffusion Language Models
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CXL-SpecKV: A Disaggregated FPGA Speculative KV-Cache for Datacenter LLM Serving
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SparK: Query-Aware Unstructured Sparsity with Recoverable KV Cache Channel Pruning
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Efficient and Adaptable Overlapping for Computation and Communication via Signaling and Reordering
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APRIL: Active Partial Rollouts in Reinforcement Learning to Tame Long-tail Generation
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Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks
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Agent Laboratory: Using LLM Agents as Research Assistants
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Agent Laboratory: Using LLM Agents as Research Assistants
