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Expanding AI Reasoning: A New Approach to Zero Reinforcement Learning for Diverse Tasks

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Advancing Patent Text Understanding with a New Benchmark and Specialized Embedding Models

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Deconstructing Vehicle Routing: A Modular Approach to Multi-Task Optimization

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Balancing Multiple Learning Tasks with Neural Tangent Kernels

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Unpacking Gradient Imbalance in Multi-Task LLM Training

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Seabed-Net: A Unified Approach to Mapping Shallow Water Depths and Habitats

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Heterogeneous Adversarial Play: A New Framework for Adaptive AI Learning

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Scaling AI Evaluation: Salesforce AI Introduces Foundational Automatic Reasoning Evaluators (FARE)

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Decoding Pet Feelings: A Continuous Approach to Understanding Animal Vocalizations

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Generalist++: A Multi-Expert Framework for Resilient AI Models

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DRGrad: Enhancing Multi-Task Learning for Personalized Recommendations

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Advanced Machine Learning Framework Enhances Alzheimer’s Disease Progression Prediction

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Enhancing Speech Recognition with Vocal Tract Movements: A New Approach to ASR

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ControlAudio: Crafting Audio with Text, Timing, and Intelligible Speech

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Optimizing Generative Auto-Bidding Through Validation-Aligned Multi-Task Learning

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Tailoring Language Models: A New Approach to Preference Optimization with Expert Mixtures

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LEXPOL: A New Framework for Multi-Task Reinforcement Learning Using Language-Guided Skill Composition

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Adaptive Shared Experts: A New Approach to Multi-Task Learning with Dynamic Knowledge Sharing

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Bridging the Accessibility Gap: How AI is Learning to Create Easy-to-Read Content

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Unlocking LLM Efficiency: Why Sharing ‘B’ is Better Than ‘A’ in LoRA Fine-Tuning

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Adaptive AI Optimizes Molecular Design in Data-Scarce Environments

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TAP: A Two-Stage Approach for Personalized Multi-Modal Federated Learning

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Guiding Small Language Models to Think: A New Approach to Reasoning Distillation

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Adaptive AI: How Neuroplasticity is Reshaping Multi-Task Demand Forecasting

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Advancing Surgical Care with Causal Machine Learning: A Personalized Approach to Treatment Decisions

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Graph Coloring for Smarter Multi-Task Learning

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Boosting Information Retrieval with Chunk-Based Knowledge Generation

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Unlocking Cross-Task Transfer in Prompt-Tuned Language Models

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H2R: Enhancing LLM Agents with Hierarchical Memory for Multi-Task Learning

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Robots Learn to Multitask: A New Approach for Handling Multiple Urgent Questions in 3D Environments

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