{"total":122,"rows":[{"id":"2303.08774","title":"GPT-4 Technical Report","created":"2023-03-15","cited_by_count":18396,"area":null},{"id":"2205.14135","title":"FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness","created":"2022-05-27","cited_by_count":3673,"area":null},{"id":"2307.08691","title":"FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning","created":"2023-07-17","cited_by_count":2598,"area":null},{"id":"2305.13048","title":"RWKV: Reinventing RNNs for the Transformer Era","created":"2023-05-22","cited_by_count":827,"area":null},{"id":"2309.10305","title":"Baichuan 2: Open Large-scale Language Models","created":"2023-09-19","cited_by_count":670,"area":null},{"id":"2307.06435","title":"A Comprehensive Overview of Large Language Models","created":"2023-07-12","cited_by_count":648,"area":null},{"id":"2306.13643","title":"LightGlue: Local Feature Matching at Light Speed","created":"2023-06-23","cited_by_count":590,"area":null},{"id":"2311.16867","title":"The Falcon Series of Open Language Models","created":"2023-11-28","cited_by_count":535,"area":null},{"id":"2212.14052","title":"Hungry Hungry Hippos: Towards Language Modeling with State Space Models","created":"2022-12-28","cited_by_count":499,"area":null},{"id":"2310.01889","title":"Ring Attention with Blockwise Transformers for Near-Infinite Context","created":"2023-10-03","cited_by_count":457,"area":null},{"id":"2407.19669","title":"mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval","created":"2024-07-29","cited_by_count":236,"area":null},{"id":"2307.06304","title":"Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution","created":"2023-07-12","cited_by_count":229,"area":null},{"id":"2402.17152","title":"Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations","created":"2024-02-27","cited_by_count":188,"area":null},{"id":"2412.05496","title":"Flex Attention: A Programming Model for Generating Optimized Attention Kernels","created":"2024-12-07","cited_by_count":185,"area":null},{"id":"2406.16838","title":"From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models","created":"2024-06-24","cited_by_count":137,"area":null},{"id":"2305.11172","title":"ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalities","created":"2023-05-18","cited_by_count":118,"area":null},{"id":"2402.05099","title":"Hydragen: High-Throughput LLM Inference with Shared Prefixes","created":"2024-02-07","cited_by_count":73,"area":null},{"id":"2311.12351","title":"Advancing Transformer Architecture in Long-Context Large Language Models: A Comprehensive Survey","created":"2023-11-21","cited_by_count":72,"area":null},{"id":"2403.05231","title":"Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance","created":"2024-03-08","cited_by_count":70,"area":null},{"id":"2202.07765","title":"General-purpose, long-context autoregressive modeling with Perceiver AR","created":"2022-02-15","cited_by_count":60,"area":null},{"id":"2304.06194","title":"SiLK -- Simple Learned Keypoints","created":"2023-04-12","cited_by_count":54,"area":null},{"id":"2311.09431","title":"Striped Attention: Faster Ring Attention for Causal Transformers","created":"2023-11-15","cited_by_count":54,"area":null},{"id":"2305.18415","title":"Geometric Algebra Transformer","created":"2023-05-28","cited_by_count":48,"area":null},{"id":"2408.07092","title":"Post-Training Sparse Attention with Double Sparsity","created":"2024-08-11","cited_by_count":45,"area":null},{"id":"2309.08586","title":"Replacing softmax with ReLU in Vision Transformers","created":"2023-09-15","cited_by_count":44,"area":null},{"id":"2404.08763","title":"CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models","created":"2024-04-12","cited_by_count":41,"area":null},{"id":"2411.09009","title":"Cut Your Losses in Large-Vocabulary Language Models","created":"2024-11-13","cited_by_count":40,"area":null},{"id":"2502.06042","title":"Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection","created":"2025-02-09","cited_by_count":35,"area":null},{"id":"2312.17482","title":"MosaicBERT: A Bidirectional Encoder Optimized for Fast Pretraining","created":"2023-12-29","cited_by_count":34,"area":null},{"id":"2505.16381","title":"PaTH Attention: Position Encoding via Accumulating Householder Transformations","created":"2025-05-22","cited_by_count":34,"area":null},{"id":"2506.10707","title":"ConTextTab: A Semantics-Aware Tabular In-Context Learner","created":"2025-06-12","cited_by_count":34,"area":null},{"id":"2412.03594","title":"BatchLLM: Optimizing Large Batched LLM Inference with Global Prefix Sharing and Throughput-oriented Token Batching","created":"2024-11-29","cited_by_count":32,"area":null},{"id":"2206.11357","title":"GACT: Activation Compressed Training for Generic Network Architectures","created":"2022-06-22","cited_by_count":31,"area":null},{"id":"2303.15724","title":"Scalable, Detailed and Mask-Free Universal Photometric Stereo","created":"2023-03-28","cited_by_count":30,"area":null},{"id":"2310.03294","title":"DISTFLASHATTN: Distributed Memory-efficient Attention for Long-context LLMs Training","created":"2023-10-05","cited_by_count":29,"area":null},{"id":"2304.03589","title":"On Efficient Training of Large-Scale Deep Learning Models: A Literature Review","created":"2023-04-07","cited_by_count":26,"area":null},{"id":"2309.14021","title":"LORD: Low Rank Decomposition Of Monolingual Code LLMs For One-Shot Compression","created":"2023-09-25","cited_by_count":26,"area":null},{"id":"2309.16354","title":"Transformer-VQ: Linear-Time Transformers via Vector Quantization","created":"2023-09-28","cited_by_count":26,"area":null},{"id":"2302.04542","title":"Efficient Attention via Control Variates","created":"2023-02-09","cited_by_count":23,"area":null},{"id":"2410.01359","title":"FlashMask: Efficient and Rich Mask Extension of FlashAttention","created":"2024-10-02","cited_by_count":20,"area":null},{"id":"2504.16922","title":"Generalized Neighborhood Attention: Multi-dimensional Sparse Attention at the Speed of Light","created":"2025-04-23","cited_by_count":18,"area":null},{"id":"2510.03346","title":"KVComm: Enabling Efficient LLM Communication through Selective KV Sharing","created":"2025-10-02","cited_by_count":18,"area":null},{"id":"2510.26493","title":"Context Engineering 2.0: The Context of Context Engineering","created":"2025-10-30","cited_by_count":18,"area":null},{"id":"2403.04690","title":"Faster Neighborhood Attention: Reducing the O(n^2) Cost of Self Attention at the Threadblock Level","created":"2024-03-07","cited_by_count":14,"area":null},{"id":"2311.04744","title":"Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers","created":"2023-11-08","cited_by_count":13,"area":null},{"id":"2402.14808","title":"RelayAttention for Efficient Large Language Model Serving with Long System Prompts","created":"2024-02-22","cited_by_count":13,"area":null},{"id":"2305.19370","title":"Blockwise Parallel Transformer for Large Context Models","created":"2023-05-30","cited_by_count":12,"area":null},{"id":"2403.07536","title":"LaB-GATr: geometric algebra transformers for large biomedical surface and volume meshes","created":"2024-03-12","cited_by_count":12,"area":null},{"id":"2410.14195","title":"Rethinking Transformer for Long Contextual Histopathology Whole Slide Image Analysis","created":"2024-10-18","cited_by_count":12,"area":null},{"id":"2402.10793","title":"An end-to-end attention-based approach for learning on graphs","created":"2024-02-16","cited_by_count":11,"area":null},{"id":"2505.12044","title":"FlashBias: Fast Computation of Attention with Bias","created":"2025-05-17","cited_by_count":11,"area":null},{"id":"2403.09347","title":"BurstAttention: An Efficient Distributed Attention Framework for Extremely Long Sequences","created":"2024-03-14","cited_by_count":10,"area":null},{"id":"2404.15653","title":"CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data","created":"2024-04-24","cited_by_count":10,"area":null},{"id":"2608.25774","title":"EXAONE Tabular 1.0 : Technical Report","created":"2026-08-26","cited_by_count":10,"area":null},{"id":"2305.14567","title":"Memory Efficient Neural Processes via Constant Memory Attention Block","created":"2023-05-23","cited_by_count":9,"area":null},{"id":"2311.00684","title":"Attention Alignment and Flexible Positional Embeddings Improve Transformer Length Extrapolation","created":"2023-11-01","cited_by_count":9,"area":null},{"id":"2403.14628","title":"Zero-Shot Multi-Object Scene Completion","created":"2024-03-21","cited_by_count":9,"area":null},{"id":"2409.16997","title":"INT-FlashAttention: Enabling Flash Attention for INT8 Quantization","created":"2024-09-25","cited_by_count":9,"area":null},{"id":"2505.20283","title":"Category-Agnostic Neural Object Rigging","created":"2025-05-26","cited_by_count":9,"area":null},{"id":"2210.07189","title":"On Compressing Sequences for Self-Supervised Speech Models","created":"2022-10-13","cited_by_count":8,"area":null},{"id":"2404.02882","title":"Linear Attention Sequence Parallelism","created":"2024-04-03","cited_by_count":8,"area":null},{"id":"2508.08435","title":"Fast weight programming and linear transformers: from machine learning to neurobiology","created":"2025-08-11","cited_by_count":8,"area":null},{"id":"2401.15496","title":"Baichuan2-Sum: Instruction Finetune Baichuan2-7B Model for Dialogue Summarization","created":"2024-01-27","cited_by_count":7,"area":null},{"id":"2404.09707","title":"Adaptive Patching for High-resolution Image Segmentation with Transformers","created":"2024-04-15","cited_by_count":6,"area":null},{"id":"2405.07395","title":"CaFA: Global Weather Forecasting with Factorized Attention on Sphere","created":"2024-05-12","cited_by_count":6,"area":null},{"id":"2405.13956","title":"Attention as an RNN","created":"2024-05-22","cited_by_count":6,"area":null},{"id":"2407.15892","title":"Mini-Sequence Transformer: Optimizing Intermediate Memory for Long Sequences Training","created":"2024-07-22","cited_by_count":6,"area":null},{"id":"2408.16978","title":"Training Ultra Long Context Language Model with Fully Pipelined Distributed Transformer","created":"2024-08-30","cited_by_count":6,"area":null},{"id":"2410.19836","title":"Upsampling DINOv2 features for unsupervised vision tasks and weakly supervised materials segmentation","created":"2024-10-20","cited_by_count":6,"area":null},{"id":"2604.21215","title":"The Recurrent Transformer: Greater Effective Depth and Efficient Decoding","created":"2026-04-23","cited_by_count":6,"area":null},{"id":"2305.18513","title":"SlimFit: Memory-Efficient Fine-Tuning of Transformer-based Models Using Training Dynamics","created":"2023-05-29","cited_by_count":5,"area":null},{"id":"2409.05477","title":"Retrofitting Temporal Graph Neural Networks with Transformer","created":"2024-09-09","cited_by_count":5,"area":null},{"id":"2409.18747","title":"Cottention: Linear Transformers With Cosine Attention","created":"2024-09-27","cited_by_count":5,"area":null},{"id":"2505.14314","title":"Low-Cost FlashAttention with Fused Exponential and Multiplication Hardware Operators","created":"2025-05-20","cited_by_count":5,"area":null},{"id":"2206.14148","title":"Memory Safe Computations with XLA Compiler","created":"2022-06-28","cited_by_count":4,"area":null},{"id":"2310.01924","title":"RoFormer for Position Aware Multiple Instance Learning in Whole Slide Image Classification","created":"2023-10-03","cited_by_count":4,"area":null},{"id":"2406.08334","title":"ProTrain: Efficient LLM Training via Memory-Aware Techniques","created":"2024-06-12","cited_by_count":4,"area":null},{"id":"2406.16424","title":"Memory-Enhanced Neural Solvers for Routing Problems","created":"2024-06-24","cited_by_count":4,"area":null},{"id":"2501.12381","title":"Parallel Sequence Modeling via Generalized Spatial Propagation Network","created":"2025-01-21","cited_by_count":4,"area":null},{"id":"2311.02382","title":"Ultra-Long Sequence Distributed Transformer","created":"2023-11-04","cited_by_count":3,"area":null},{"id":"2311.12885","title":"Long-MIL: Scaling Long Contextual Multiple Instance Learning for Histopathology Whole Slide Image Analysis","created":"2023-11-21","cited_by_count":3,"area":null},{"id":"2403.11026","title":"EfficientMorph: Parameter-Efficient Transformer-Based Architecture for 3D Image Registration","created":"2024-03-16","cited_by_count":3,"area":null},{"id":"2408.04632","title":"Arctic-TILT. Business Document Understanding at Sub-Billion Scale","created":"2024-08-08","cited_by_count":3,"area":null},{"id":"2410.16663","title":"FastAttention: Extend FlashAttention2 to NPUs and Low-resource GPUs","created":"2024-10-22","cited_by_count":3,"area":null},{"id":"2501.11847","title":"A Survey on Memory-Efficient Transformer-Based Model Training in AI for Science","created":"2025-01-21","cited_by_count":3,"area":null},{"id":"2607.14952","title":"LongStraw: Long-Context RL Beyond 2M Tokens under a Fixed GPU Budget","created":"2026-07-16","cited_by_count":3,"area":null},{"id":"2503.00958","title":"Layered Insights: Generalizable Analysis of Authorial Style by Leveraging All Transformer Layers","created":"2025-03-02","cited_by_count":2,"area":null},{"id":"2503.10571","title":"Radar: Fast Long-Context Decoding for Any Transformer","created":"2025-03-13","cited_by_count":2,"area":null},{"id":"2505.14201","title":"FLASH-D: FlashAttention with Hidden Softmax Division","created":"2025-05-20","cited_by_count":2,"area":null},{"id":"2507.01004","title":"ZeCO: Zero Communication Overhead Sequence Parallelism for Linear Attention","created":"2025-07-01","cited_by_count":2,"area":null},{"id":"2507.10618","title":"Compute Requirements for Algorithmic Innovation in Frontier AI Models","created":"2025-07-13","cited_by_count":2,"area":null},{"id":"2507.16676","title":"Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers","created":"2025-07-22","cited_by_count":2,"area":null},{"id":"2511.08028","title":"Generalizable Insights for Graph Transformers in Theory and Practice","created":"2025-11-11","cited_by_count":2,"area":null},{"id":"2410.00215","title":"Characterizing and Efficiently Accelerating Multimodal Generation Model Inference","created":"2024-09-30","cited_by_count":1,"area":null},{"id":"2506.09163","title":"Scalable Spatiotemporal Inference with Biased Scan Attention Transformer Neural Processes","created":"2025-06-10","cited_by_count":1,"area":null},{"id":"2604.02654","title":"Drift-Resilient Temporal Priors for Visual Tracking","created":"2026-04-03","cited_by_count":1,"area":null},{"id":"2606.08204","title":"Neural Field Tokenizations with Hierarchy and Spatial Locality Priors","created":"2026-06-06","cited_by_count":1,"area":null},{"id":"2312.15412","title":"CARSS: Cooperative Attention-guided Reinforcement Subpath Synthesis for Solving Traveling Salesman Problem","created":"2023-12-24","cited_by_count":0,"area":null},{"id":"2401.02744","title":"MAMI: Multi-Attentional Mutual-Information for Long Sequence Neuron Captioning","created":"2024-01-05","cited_by_count":0,"area":null},{"id":"2401.10652","title":"AutoChunk: Automated Activation Chunk for Memory-Efficient Long Sequence Inference","created":"2024-01-19","cited_by_count":0,"area":null}],"next_cursor":"100"}