{"total":265,"rows":[{"id":"2303.15389","title":"EVA-CLIP: Improved Training Techniques for CLIP at Scale","created":"2023-03-27","cited_by_count":798,"area":null},{"id":"2112.12750","title":"SLIP: Self-supervision meets Language-Image Pre-training","created":"2021-12-23","cited_by_count":436,"area":null},{"id":"2303.11331","title":"EVA-02: A Visual Representation for Neon Genesis","created":"2023-03-20","cited_by_count":381,"area":null},{"id":"2412.00081","title":"Task Singular Vectors: Reducing Task Interference in Model Merging","created":"2024-11-26","cited_by_count":147,"area":null},{"id":"2405.07813","title":"Localizing Task Information for Improved Model Merging and Compression","created":"2024-05-13","cited_by_count":131,"area":null},{"id":"2402.04252","title":"EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters","created":"2024-02-06","cited_by_count":99,"area":null},{"id":"2502.04959","title":"No Task Left Behind: Isotropic Model Merging with Common and Task-Specific Subspaces","created":"2025-02-07","cited_by_count":96,"area":null},{"id":"2104.00232","title":"Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression Recognition","created":"2021-04-01","cited_by_count":89,"area":null},{"id":"2110.11316","title":"CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP","created":"2021-10-21","cited_by_count":89,"area":null},{"id":"2204.09308","title":"A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglement","created":"2022-04-20","cited_by_count":87,"area":null},{"id":"2108.11116","title":"TransFER: Learning Relation-aware Facial Expression Representations with Transformers","created":"2021-08-25","cited_by_count":85,"area":null},{"id":"2211.06679","title":"AltCLIP: Altering the Language Encoder in CLIP for Extended Language Capabilities","created":"2022-11-12","cited_by_count":85,"area":null},{"id":"2307.07961","title":"EmoSet: A Large-scale Visual Emotion Dataset with Rich Attributes","created":"2023-07-16","cited_by_count":82,"area":null},{"id":"2203.16329","title":"Parameter-efficient Model Adaptation for Vision Transformers","created":"2022-03-29","cited_by_count":81,"area":null},{"id":"2207.10299","title":"Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition","created":"2022-07-21","cited_by_count":67,"area":null},{"id":"2204.04083","title":"POSTER: A Pyramid Cross-Fusion Transformer Network for Facial Expression Recognition","created":"2022-04-08","cited_by_count":49,"area":null},{"id":"2107.02823","title":"Deep Learning for Micro-expression Recognition: A Survey","created":"2021-07-06","cited_by_count":43,"area":null},{"id":"2410.17146","title":"LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model Merging","created":"2024-10-22","cited_by_count":41,"area":null},{"id":"2312.04293","title":"GPT-4V with Emotion: A Zero-shot Benchmark for Generalized Emotion Recognition","created":"2023-12-07","cited_by_count":38,"area":null},{"id":"2212.05463","title":"Vision Transformer with Attentive Pooling for Robust Facial Expression Recognition","created":"2022-12-11","cited_by_count":35,"area":null},{"id":"2104.03509","title":"Py-Feat: Python Facial Expression Analysis Toolbox","created":"2021-04-08","cited_by_count":33,"area":null},{"id":"2111.08687","title":"INTERN: A New Learning Paradigm Towards General Vision","created":"2021-11-16","cited_by_count":33,"area":null},{"id":"2304.08981","title":"MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning","created":"2023-04-18","cited_by_count":33,"area":null},{"id":"2303.00106","title":"The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning","created":"2023-02-28","cited_by_count":27,"area":null},{"id":"2109.01812","title":"Stimuli-Aware Visual Emotion Analysis","created":"2021-09-04","cited_by_count":26,"area":null},{"id":"2404.05052","title":"Facial Affective Behavior Analysis with Instruction Tuning","created":"2024-04-07","cited_by_count":26,"area":null},{"id":"2111.12890","title":"V2C: Visual Voice Cloning","created":"2021-11-25","cited_by_count":24,"area":null},{"id":"2402.01355","title":"FindingEmo: An Image Dataset for Emotion Recognition in the Wild","created":"2024-02-02","cited_by_count":22,"area":null},{"id":"2407.03418","title":"HEMM: Holistic Evaluation of Multimodal Foundation Models","created":"2024-07-03","cited_by_count":21,"area":null},{"id":"2105.03588","title":"Facial Emotion Recognition: State of the Art Performance on FER2013","created":"2021-05-08","cited_by_count":20,"area":null},{"id":"2108.03427","title":"Learning Facial Representations from the Cycle-consistency of Face","created":"2021-08-07","cited_by_count":20,"area":null},{"id":"2211.13490","title":"Pose-disentangled Contrastive Learning for Self-supervised Facial Representation","created":"2022-11-24","cited_by_count":17,"area":null},{"id":"2307.09023","title":"LA-Net: Landmark-Aware Learning for Reliable Facial Expression Recognition under Label Noise","created":"2023-07-18","cited_by_count":17,"area":null},{"id":"2309.06922","title":"Hydra: Multi-head Low-rank Adaptation for Parameter Efficient Fine-tuning","created":"2023-09-13","cited_by_count":17,"area":null},{"id":"2310.19636","title":"Leave No Stone Unturned: Mine Extra Knowledge for Imbalanced Facial Expression Recognition","created":"2023-10-30","cited_by_count":17,"area":null},{"id":"2403.02138","title":"Self-Supervised Facial Representation Learning with Facial Region Awareness","created":"2024-03-04","cited_by_count":17,"area":null},{"id":"2304.00058","title":"Weakly-Supervised Text-driven Contrastive Learning for Facial Behavior Understanding","created":"2023-03-31","cited_by_count":16,"area":null},{"id":"2306.03715","title":"Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability","created":"2023-06-06","cited_by_count":16,"area":null},{"id":"2404.14606","title":"Cross-Task Multi-Branch Vision Transformer for Facial Expression and Mask Wearing Classification","created":"2024-04-22","cited_by_count":16,"area":null},{"id":"2506.16895","title":"With Limited Data for Multimodal Alignment, Let the STRUCTURE Guide You","created":"2025-06-20","cited_by_count":16,"area":null},{"id":"2103.15599","title":"Graph-based Facial Affect Analysis: A Review","created":"2021-03-29","cited_by_count":14,"area":null},{"id":"2407.17331","title":"Multi-label Cluster Discrimination for Visual Representation Learning","created":"2024-07-24","cited_by_count":14,"area":null},{"id":"2505.11883","title":"MINGLE: Mixture of Null-Space Gated Low-Rank Experts for Test-Time Continual Model Merging","created":"2025-05-17","cited_by_count":14,"area":null},{"id":"2107.14203","title":"Did the Model Change? Efficiently Assessing Machine Learning API Shifts","created":"2021-07-29","cited_by_count":13,"area":null},{"id":"2201.01709","title":"The Effect of Model Compression on Fairness in Facial Expression Recognition","created":"2022-01-05","cited_by_count":13,"area":null},{"id":"2303.15889","title":"Metrics for Dataset Demographic Bias: A Case Study on Facial Expression Recognition","created":"2023-03-28","cited_by_count":13,"area":null},{"id":"2307.10184","title":"A Dual Stealthy Backdoor: From Both Spatial and Frequency Perspectives","created":"2023-07-03","cited_by_count":13,"area":null},{"id":"2403.09500","title":"Faceptor: A Generalist Model for Face Perception","created":"2024-03-14","cited_by_count":13,"area":null},{"id":"2406.03280","title":"FusionBench: A Unified Library and Comprehensive Benchmark for Deep Model Fusion","created":"2024-06-05","cited_by_count":13,"area":null},{"id":"2105.07484","title":"Leveraging Semantic Scene Characteristics and Multi-Stream Convolutional Architectures in a Contextual Approach for Video-Based Visual Emotion Recognition in the Wild","created":"2021-05-16","cited_by_count":12,"area":null},{"id":"2106.03487","title":"Exploiting Emotional Dependencies with Graph Convolutional Networks for Facial Expression Recognition","created":"2021-06-07","cited_by_count":12,"area":null},{"id":"2203.14463","title":"Large-scale Bilingual Language-Image Contrastive Learning","created":"2022-03-28","cited_by_count":12,"area":null},{"id":"2205.14361","title":"Boosting Facial Expression Recognition by A Semi-Supervised Progressive Teacher","created":"2022-05-28","cited_by_count":12,"area":null},{"id":"2503.19851","title":"Towards Online Multi-Modal Social Interaction Understanding","created":"2025-03-25","cited_by_count":12,"area":null},{"id":"2208.08106","title":"Disentangling Identity and Pose for Facial Expression Recognition","created":"2022-08-17","cited_by_count":11,"area":null},{"id":"2312.05632","title":"Subject-Based Domain Adaptation for Facial Expression Recognition","created":"2023-12-09","cited_by_count":11,"area":null},{"id":"2508.03121","title":"RegMean++: Enhancing Effectiveness and Generalization of Regression Mean for Model Merging","created":"2025-08-05","cited_by_count":11,"area":null},{"id":"2212.07144","title":"Uncertain Facial Expression Recognition via Multi-task Assisted Correction","created":"2022-12-14","cited_by_count":10,"area":null},{"id":"2205.10049","title":"Assessing Demographic Bias Transfer from Dataset to Model: A Case Study in Facial Expression Recognition","created":"2022-05-20","cited_by_count":9,"area":null},{"id":"2409.10545","title":"ResEmoteNet: Bridging Accuracy and Loss Reduction in Facial Emotion Recognition","created":"2024-09-01","cited_by_count":9,"area":null},{"id":"2410.22506","title":"AffectNet+: A Database for Enhancing Facial Expression Recognition with Soft-Labels","created":"2024-10-29","cited_by_count":9,"area":null},{"id":"2503.22178","title":"AdaRank: Adaptive Rank Pruning for Enhanced Model Merging","created":"2025-03-28","cited_by_count":9,"area":null},{"id":"2207.05577","title":"Learning from Label Relationships in Human Affect","created":"2022-07-12","cited_by_count":8,"area":null},{"id":"2210.05332","title":"Gender Stereotyping Impact in Facial Expression Recognition","created":"2022-10-11","cited_by_count":8,"area":null},{"id":"2303.12997","title":"FER-former: Multi-modal Transformer for Facial Expression Recognition","created":"2023-03-23","cited_by_count":8,"area":null},{"id":"2410.08049","title":"Scaling Up Your Kernels: Large Kernel Design in ConvNets towards Universal Representations","created":"2024-10-10","cited_by_count":8,"area":null},{"id":"2509.21413","title":"Null-Space Filtering for Data-Free Continual Model Merging: Preserving Stability, Promoting Plasticity","created":"2025-09-25","cited_by_count":8,"area":null},{"id":"2603.06242","title":"DC-Merge: Improving Model Merging with Directional Consistency","created":"2026-03-06","cited_by_count":8,"area":null},{"id":"2103.13598","title":"Recent Advances in Large Margin Learning","created":"2021-03-25","cited_by_count":7,"area":null},{"id":"2111.07224","title":"Local Multi-Head Channel Self-Attention for Facial Expression Recognition","created":"2021-11-14","cited_by_count":7,"area":null},{"id":"2205.06102","title":"Tensor-based Emotion Editing in the StyleGAN Latent Space","created":"2022-05-12","cited_by_count":7,"area":null},{"id":"2305.07665","title":"A Comprehensive Survey on Affective Computing; Challenges, Trends, Applications, and Future Directions","created":"2023-05-08","cited_by_count":7,"area":null},{"id":"2306.09626","title":"PAtt-Lite: Lightweight Patch and Attention MobileNet for Challenging Facial Expression Recognition","created":"2023-06-16","cited_by_count":7,"area":null},{"id":"2310.13683","title":"CAPIVARA: Cost-Efficient Approach for Improving Multilingual CLIP Performance on Low-Resource Languages","created":"2023-10-20","cited_by_count":7,"area":null},{"id":"2408.17198","title":"Towards Symbolic XAI -- Explanation Through Human Understandable Logical Relationships Between Features","created":"2024-08-30","cited_by_count":7,"area":null},{"id":"2409.08907","title":"Affective Computing Has Changed: The Foundation Model Disruption","created":"2024-09-13","cited_by_count":7,"area":null},{"id":"2412.07116","title":"A Review of Human Emotion Synthesis Based on Generative Technology","created":"2024-12-10","cited_by_count":7,"area":null},{"id":"2601.22285","title":"Demystifying Mergeability: Interpretable Properties to Predict Model Merging Success","created":"2026-01-29","cited_by_count":7,"area":null},{"id":"2602.20208","title":"Model Merging in the Essential Subspace","created":"2026-02-23","cited_by_count":7,"area":null},{"id":"2112.02487","title":"Face Trees for Expression Recognition","created":"2021-12-05","cited_by_count":6,"area":null},{"id":"2304.05634","title":"How you feelin'? Learning Emotions and Mental States in Movie Scenes","created":"2023-04-12","cited_by_count":6,"area":null},{"id":"2403.11757","title":"Efficient Feature Extraction and Late Fusion Strategy for Audiovisual Emotional Mimicry Intensity Estimation","created":"2024-03-18","cited_by_count":6,"area":null},{"id":"2404.14975","title":"CAGE: Circumplex Affect Guided Expression Inference","created":"2024-04-23","cited_by_count":6,"area":null},{"id":"2408.10614","title":"Generalizable Facial Expression Recognition","created":"2024-08-20","cited_by_count":6,"area":null},{"id":"2408.16907","title":"Ig3D: Integrating 3D Face Representations in Facial Expression Inference","created":"2024-08-29","cited_by_count":6,"area":null},{"id":"2502.11049","title":"Faces of Fairness: Examining Bias in Facial Expression Recognition Datasets and Models","created":"2025-02-16","cited_by_count":6,"area":null},{"id":"2603.02945","title":"ACE-Merging: Data-Free Model Merging with Adaptive Covariance Estimation","created":"2026-03-03","cited_by_count":6,"area":null},{"id":"2108.11754","title":"Training and Profiling a Pediatric Emotion Recognition Classifier on Mobile Devices","created":"2021-08-22","cited_by_count":5,"area":null},{"id":"2207.01059","title":"Identifying the Context Shift between Test Benchmarks and Production Data","created":"2022-07-03","cited_by_count":5,"area":null},{"id":"2210.05246","title":"Cluster-level pseudo-labelling for source-free cross-domain facial expression recognition","created":"2022-10-11","cited_by_count":5,"area":null},{"id":"2305.13782","title":"Images in Language Space: Exploring the Suitability of Large Language Models for Vision & Language Tasks","created":"2023-05-23","cited_by_count":5,"area":null},{"id":"2309.00138","title":"Fuzzy Approach for Audio-Video Emotion Recognition in Computer Games for Children","created":"2023-08-31","cited_by_count":5,"area":null},{"id":"2312.14626","title":"DSAP: Analyzing Bias Through Demographic Comparison of Datasets","created":"2023-12-22","cited_by_count":5,"area":null},{"id":"2406.17405","title":"Less can be more: representational vs. stereotypical gender bias in facial expression recognition","created":"2024-06-25","cited_by_count":5,"area":null},{"id":"2412.17616","title":"Facial Expression Analysis and Its Potentials in IoT Systems: A Contemporary Survey","created":"2024-12-23","cited_by_count":5,"area":null},{"id":"2503.06921","title":"Task Vector Quantization for Memory-Efficient Model Merging","created":"2025-03-10","cited_by_count":5,"area":null},{"id":"2503.12649","title":"FW-Merging: Scaling Model Merging with Frank-Wolfe Optimization","created":"2025-03-16","cited_by_count":5,"area":null},{"id":"2504.05342","title":"MASS: MoErging through Adaptive Subspace Selection","created":"2025-04-06","cited_by_count":5,"area":null},{"id":"2602.05536","title":"When Shared Knowledge Hurts: Spectral Over-Accumulation in Model Merging","created":"2026-02-05","cited_by_count":5,"area":null},{"id":"2605.13030","title":"FeatCal: Feature Calibration for Post-Merging Models","created":"2026-05-13","cited_by_count":5,"area":null}],"next_cursor":"100"}