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661,570 papers248,326 code links4,818 tasks

Papers

Showing 24012425 of 177340 papers

TitleStatusHype
PointNeXt: Revisiting PointNet++ with Improved Training and Scaling StrategiesCode3
Bidirectional Multi-Scale Implicit Neural Representations for Image DerainingCode3
Accelerating Transformer Inference for Translation via Parallel DecodingCode3
DiM: Diffusion Mamba for Efficient High-Resolution Image SynthesisCode3
GoT: Unleashing Reasoning Capability of Multimodal Large Language Model for Visual Generation and EditingCode3
ConceptAttention: Diffusion Transformers Learn Highly Interpretable FeaturesCode3
A Distractor-Aware Memory for Visual Object Tracking with SAM2Code3
TAPIP3D: Tracking Any Point in Persistent 3D GeometryCode3
CharacterEval: A Chinese Benchmark for Role-Playing Conversational Agent EvaluationCode3
Data Generation for Hardware-Friendly Post-Training QuantizationCode3
LLMmap: Fingerprinting For Large Language ModelsCode3
SongComposer: A Large Language Model for Lyric and Melody Generation in Song CompositionCode3
PRefLexOR: Preference-based Recursive Language Modeling for Exploratory Optimization of Reasoning and Agentic ThinkingCode3
ExCoT: Optimizing Reasoning for Text-to-SQL with Execution FeedbackCode3
MagicPIG: LSH Sampling for Efficient LLM GenerationCode3
MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMsCode3
Qihoo-T2X: An Efficient Proxy-Tokenized Diffusion Transformer for Text-to-Any-TaskCode3
What Language Model to Train if You Have One Million GPU Hours?Code3
FiTv2: Scalable and Improved Flexible Vision Transformer for Diffusion ModelCode3
An Evolved Universal Transformer MemoryCode3
Instruct-IPT: All-in-One Image Processing Transformer via Weight ModulationCode3
DFormerv2: Geometry Self-Attention for RGBD Semantic SegmentationCode3
SegFormer3D: an Efficient Transformer for 3D Medical Image SegmentationCode3
CATANet: Efficient Content-Aware Token Aggregation for Lightweight Image Super-ResolutionCode3
Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few LabelsCode3
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