{"total":375,"rows":[{"id":"2310.02575","title":"AdaMerging: Adaptive Model Merging for Multi-Task Learning","created":"2023-10-04","cited_by_count":252,"area":null},{"id":"2104.08212","title":"MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale","created":"2021-04-16","cited_by_count":229,"area":null},{"id":"2109.04617","title":"Efficiently Identifying Task Groupings for Multi-Task Learning","created":"2021-09-10","cited_by_count":222,"area":null},{"id":"2202.01017","title":"Multi-Task Learning as a Bargaining Game","created":"2022-02-02","cited_by_count":215,"area":null},{"id":"2102.10772","title":"UniT: Multimodal Multitask Learning with a Unified Transformer","created":"2021-02-22","cited_by_count":195,"area":null},{"id":"2102.06177","title":"Multi-Task Reinforcement Learning with Context-based Representations","created":"2021-02-11","cited_by_count":174,"area":null},{"id":"2104.08835","title":"CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP","created":"2021-04-18","cited_by_count":142,"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":"2210.14793","title":"M$^3$ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design","created":"2022-10-26","cited_by_count":98,"area":"moe"},{"id":"2209.04899","title":"Instruction-driven history-aware policies for robotic manipulations","created":"2022-09-11","cited_by_count":94,"area":null},{"id":"2309.15698","title":"Deep Model Fusion: A Survey","created":"2023-09-27","cited_by_count":91,"area":null},{"id":"2103.02631","title":"RotoGrad: Gradient Homogenization in Multitask Learning","created":"2021-03-03","cited_by_count":83,"area":null},{"id":"2306.03792","title":"FAMO: Fast Adaptive Multitask Optimization","created":"2023-06-06","cited_by_count":78,"area":null},{"id":"2202.03091","title":"Auto-Lambda: Disentangling Dynamic Task Relationships","created":"2022-02-07","cited_by_count":73,"area":null},{"id":"2104.04132","title":"Replay in Deep Learning: Current Approaches and Missing Biological Elements","created":"2021-04-01","cited_by_count":72,"area":null},{"id":"2606.30406","title":"MOPD: Multi-Teacher On-Policy Distillation for Capability Integration in LLM Post-Training","created":"2026-06-29","cited_by_count":72,"area":"distill"},{"id":"2206.04674","title":"Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEs","created":"2022-06-09","cited_by_count":58,"area":"moe"},{"id":"2107.05782","title":"Improving Speech Translation by Understanding and Learning from the Auxiliary Text Translation Task","created":"2021-07-12","cited_by_count":54,"area":null},{"id":"2406.09406","title":"4M-21: An Any-to-Any Vision Model for Tens of Tasks and Modalities","created":"2024-06-13","cited_by_count":52,"area":null},{"id":"2408.07057","title":"A Survey on Model MoErging: Recycling and Routing Among Specialized Experts for Collaborative Learning","created":"2024-08-13","cited_by_count":52,"area":null},{"id":"2211.11720","title":"Multitask Vision-Language Prompt Tuning","created":"2022-11-21","cited_by_count":51,"area":"mllm"},{"id":"2302.11289","title":"Recon: Reducing Conflicting Gradients from the Root for Multi-Task Learning","created":"2023-02-22","cited_by_count":51,"area":null},{"id":"2210.03885","title":"Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-Experts","created":"2022-10-08","cited_by_count":50,"area":"moe"},{"id":"2205.03805","title":"A Closer Look at Few-shot Image Generation","created":"2022-05-08","cited_by_count":49,"area":null},{"id":"2205.08303","title":"MulT: An End-to-End Multitask Learning Transformer","created":"2022-05-17","cited_by_count":48,"area":null},{"id":"2103.13392","title":"Scalable Pareto Front Approximation for Deep Multi-Objective Learning","created":"2021-03-24","cited_by_count":45,"area":null},{"id":"2311.05709","title":"OmniVec: Learning robust representations with cross modal sharing","created":"2023-11-07","cited_by_count":44,"area":null},{"id":"2204.03508","title":"A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methods","created":"2022-04-07","cited_by_count":42,"area":null},{"id":"2402.02511","title":"PoCo: Policy Composition from and for Heterogeneous Robot Learning","created":"2024-02-04","cited_by_count":42,"area":null},{"id":"2312.08636","title":"MmAP : Multi-modal Alignment Prompt for Cross-domain Multi-task Learning","created":"2023-12-14","cited_by_count":41,"area":null},{"id":"2507.04701","title":"XiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQL","created":"2025-07-07","cited_by_count":40,"area":null},{"id":"2207.10430","title":"The Neural Race Reduction: Dynamics of Abstraction in Gated Networks","created":"2022-07-21","cited_by_count":37,"area":null},{"id":"2211.03044","title":"Tuning Language Models as Training Data Generators for Augmentation-Enhanced Few-Shot Learning","created":"2022-11-06","cited_by_count":36,"area":null},{"id":"2106.02705","title":"Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning","created":"2021-06-04","cited_by_count":34,"area":null},{"id":"2303.12512","title":"Sibling-Attack: Rethinking Transferable Adversarial Attacks against Face Recognition","created":"2023-03-22","cited_by_count":34,"area":null},{"id":"2207.04526","title":"Efficient Multi-Task RGB-D Scene Analysis for Indoor Environments","created":"2022-07-10","cited_by_count":33,"area":null},{"id":"2306.00354","title":"Addressing Negative Transfer in Diffusion Models","created":"2023-06-01","cited_by_count":33,"area":"diffusion"},{"id":"2105.07830","title":"Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation","created":"2021-05-17","cited_by_count":32,"area":null},{"id":"2304.07939","title":"Leveraging sparse and shared feature activations for disentangled representation learning","created":"2023-04-17","cited_by_count":32,"area":null},{"id":"2203.01311","title":"High-Modality Multimodal Transformer: Quantifying Modality & Interaction Heterogeneity for High-Modality Representation Learning","created":"2022-03-02","cited_by_count":31,"area":null},{"id":"2312.10165","title":"Test-Time Domain Adaptation by Learning Domain-Aware Batch Normalization","created":"2023-12-15","cited_by_count":31,"area":null},{"id":"2209.08953","title":"Effective Adaptation in Multi-Task Co-Training for Unified Autonomous Driving","created":"2022-09-19","cited_by_count":30,"area":"driving"},{"id":"2210.09759","title":"Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models","created":"2022-10-18","cited_by_count":29,"area":null},{"id":"2303.14969","title":"Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matching","created":"2023-03-27","cited_by_count":29,"area":null},{"id":"2112.09081","title":"CrossLoc: Scalable Aerial Localization Assisted by Multimodal Synthetic Data","created":"2021-12-16","cited_by_count":28,"area":null},{"id":"2205.09797","title":"Improving Multi-Task Generalization via Regularizing Spurious Correlation","created":"2022-05-19","cited_by_count":28,"area":null},{"id":"2301.12618","title":"ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning","created":"2023-01-30","cited_by_count":28,"area":null},{"id":"2303.02506","title":"Prismer: A Vision-Language Model with Multi-Task Experts","created":"2023-03-04","cited_by_count":28,"area":"mllm"},{"id":"2308.12029","title":"Dual-Balancing for Multi-Task Learning","created":"2023-08-23","cited_by_count":27,"area":null},{"id":"2206.08927","title":"DenseMTL: Cross-task Attention Mechanism for Dense Multi-task Learning","created":"2022-06-17","cited_by_count":25,"area":null},{"id":"2202.02299","title":"Multi-task head pose estimation in-the-wild","created":"2022-02-04","cited_by_count":23,"area":null},{"id":"2110.14202","title":"Revisit Multimodal Meta-Learning through the Lens of Multi-Task Learning","created":"2021-10-27","cited_by_count":22,"area":null},{"id":"2202.09852","title":"Cross-Task Knowledge Distillation in Multi-Task Recommendation","created":"2022-02-20","cited_by_count":22,"area":"distill"},{"id":"2101.01896","title":"Taxonomy Completion via Triplet Matching Network","created":"2021-01-06","cited_by_count":21,"area":null},{"id":"2106.09063","title":"Specializing Multilingual Language Models: An Empirical Study","created":"2021-06-16","cited_by_count":21,"area":null},{"id":"2407.05005","title":"Personalized Federated Domain-Incremental Learning based on Adaptive Knowledge Matching","created":"2024-07-06","cited_by_count":21,"area":null},{"id":"2303.14582","title":"Identification of Negative Transfers in Multitask Learning Using Surrogate Models","created":"2023-03-25","cited_by_count":20,"area":null},{"id":"2409.06091","title":"Scalable Multitask Learning Using Gradient-based Estimation of Task Affinity","created":"2024-09-09","cited_by_count":20,"area":null},{"id":"2212.06301","title":"Egocentric Video Task Translation","created":"2022-12-13","cited_by_count":19,"area":null},{"id":"2310.08910","title":"Scalarization for Multi-Task and Multi-Domain Learning at Scale","created":"2023-10-13","cited_by_count":19,"area":null},{"id":"2501.10945","title":"Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond","created":"2025-01-19","cited_by_count":18,"area":null},{"id":"2110.13076","title":"AutoMTL: A Programming Framework for Automating Efficient Multi-Task Learning","created":"2021-10-25","cited_by_count":17,"area":null},{"id":"2110.15053","title":"Adversarial Robustness in Multi-Task Learning: Promises and Illusions","created":"2021-10-26","cited_by_count":17,"area":null},{"id":"2402.03183","title":"Predicting Configuration Performance in Multiple Environments with Sequential Meta-learning","created":"2024-02-05","cited_by_count":17,"area":null},{"id":"2407.14032","title":"Semantic-CC: Boosting Remote Sensing Image Change Captioning via Foundational Knowledge and Semantic Guidance","created":"2024-07-19","cited_by_count":17,"area":null},{"id":"2502.11986","title":"Selective Task Group Updates for Multi-Task Optimization","created":"2025-02-17","cited_by_count":17,"area":null},{"id":"2108.07926","title":"Collaboration Equilibrium in Federated Learning","created":"2021-08-18","cited_by_count":16,"area":null},{"id":"2405.19650","title":"Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization","created":"2024-05-30","cited_by_count":16,"area":null},{"id":"2406.18038","title":"MT2ST: Adaptive Multi-Task to Single-Task Learning","created":"2024-06-26","cited_by_count":16,"area":null},{"id":"2306.14009","title":"Boosting Multitask Learning on Graphs through Higher-Order Task Affinities","created":"2023-06-24","cited_by_count":15,"area":null},{"id":"2403.01197","title":"DMoERM: Recipes of Mixture-of-Experts for Effective Reward Modeling","created":"2024-03-02","cited_by_count":15,"area":"alignment"},{"id":"2106.13409","title":"Generative Modeling for Multi-task Visual Learning","created":"2021-06-25","cited_by_count":14,"area":null},{"id":"2206.04662","title":"DiSparse: Disentangled Sparsification for Multitask Model Compression","created":"2022-06-09","cited_by_count":14,"area":null},{"id":"2306.10155","title":"Fairness in Multi-Task Learning via Wasserstein Barycenters","created":"2023-06-16","cited_by_count":14,"area":null},{"id":"2308.12372","title":"Vision Transformer Adapters for Generalizable Multitask Learning","created":"2023-08-23","cited_by_count":14,"area":null},{"id":"2601.22384","title":"Graph is a Substrate Across Data Modalities","created":"2026-01-29","cited_by_count":14,"area":null},{"id":"2311.00164","title":"Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis","created":"2023-10-31","cited_by_count":13,"area":null},{"id":"2401.10222","title":"Supervised Fine-tuning in turn Improves Visual Foundation Models","created":"2024-01-18","cited_by_count":13,"area":null},{"id":"2404.02415","title":"What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases","created":"2024-04-03","cited_by_count":13,"area":"mllm"},{"id":"2206.00686","title":"Federated Learning in Non-IID Settings Aided by Differentially Private Synthetic Data","created":"2022-06-01","cited_by_count":12,"area":null},{"id":"2301.13501","title":"Auxiliary Learning as an Asymmetric Bargaining Game","created":"2023-01-31","cited_by_count":12,"area":null},{"id":"2403.09066","title":"Hyperparameters in Continual Learning: A Reality Check","created":"2024-03-14","cited_by_count":12,"area":null},{"id":"2407.12273","title":"GRIDS: Grouped Multiple-Degradation Restoration with Image Degradation Similarity","created":"2024-07-17","cited_by_count":12,"area":null},{"id":"2108.02221","title":"Deep multi-task mining Calabi-Yau four-folds","created":"2021-08-04","cited_by_count":11,"area":null},{"id":"2112.02252","title":"Channel Exchanging Networks for Multimodal and Multitask Dense Image Prediction","created":"2021-12-04","cited_by_count":11,"area":null},{"id":"2310.01362","title":"Robot Fleet Learning via Policy Merging","created":"2023-10-02","cited_by_count":11,"area":null},{"id":"2402.04005","title":"Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning","created":"2024-02-06","cited_by_count":11,"area":null},{"id":"2404.06486","title":"GO4Align: Group Optimization for Multi-Task Alignment","created":"2024-04-09","cited_by_count":11,"area":null},{"id":"2505.05279","title":"MTL-UE: Learning to Learn Nothing for Multi-Task Learning","created":"2025-05-08","cited_by_count":11,"area":null},{"id":"2101.11287","title":"Language Modelling as a Multi-Task Problem","created":"2021-01-27","cited_by_count":10,"area":null},{"id":"2109.07591","title":"On the Complementarity of Data Selection and Fine Tuning for Domain Adaptation","created":"2021-09-15","cited_by_count":10,"area":null},{"id":"2203.00517","title":"Multi-task Learning Approach for Modulation and Wireless Signal Classification for 5G and Beyond: Edge Deployment via Model Compression","created":"2022-02-26","cited_by_count":10,"area":null},{"id":"2204.05393","title":"Improving Few-Shot Part Segmentation using Coarse Supervision","created":"2022-04-11","cited_by_count":10,"area":null},{"id":"2206.04669","title":"Beyond RGB: Scene-Property Synthesis with Neural Radiance Fields","created":"2022-06-09","cited_by_count":10,"area":null},{"id":"2105.08190","title":"Graph Neural Networks for Knowledge Enhanced Visual Representation of Paintings","created":"2021-05-17","cited_by_count":9,"area":null},{"id":"2303.06856","title":"Dynamic Neural Network for Multi-Task Learning Searching across Diverse Network Topologies","created":"2023-03-13","cited_by_count":9,"area":null},{"id":"2306.02556","title":"Improved Active Multi-Task Representation Learning via Lasso","created":"2023-06-05","cited_by_count":9,"area":null},{"id":"2307.11285","title":"MAS: Towards Resource-Efficient Federated Multiple-Task Learning","created":"2023-07-21","cited_by_count":9,"area":null},{"id":"2311.12682","title":"Transferring to Real-World Layouts: A Depth-aware Framework for Scene Adaptation","created":"2023-11-21","cited_by_count":9,"area":null},{"id":"2402.11141","title":"Semantically-aware Neural Radiance Fields for Visual Scene Understanding: A Comprehensive Review","created":"2024-02-17","cited_by_count":9,"area":null}],"next_cursor":"100"}