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arXiv:2602.23447v1 Announce Type: cross Abstract: Detection of rare lesions in whole-body CT is fundamentally limited by extreme class imbalance and low target-to-volume ratios, producing precision …
arXiv:2602.23455v1 Announce Type: cross Abstract: Lightweight neural network accelerators are essential for edge devices with limited resources and power constraints. While quantization and binarization can …
arXiv:2602.23468v1 Announce Type: cross Abstract: Multi-Agent Path Finding (MAPF) aims to move agents from their start to goal vertices on a graph. Lifelong MAPF (LMAPF) …
arXiv:2602.23499v1 Announce Type: cross Abstract: Collecting a high-quality dataset is a critical task that demands meticulous attention to detail, as overlooking certain aspects can render …
arXiv:2602.23440v1 Announce Type: new Abstract: Training large language models to reason with search engines via reinforcement learning is hindered by a fundamental credit assignment problem: …
arXiv:2602.23452v1 Announce Type: new Abstract: Scientific research relies on accurate citation for attribution and integrity, yet large language models (LLMs) introduce a new risk: fabricated …
arXiv:2602.23479v1 Announce Type: new Abstract: Though patients are increasingly granted digital access to their electronic health records (EHRs), existing interfaces may not support precise, trustworthy …
arXiv:2602.23481v1 Announce Type: new Abstract: Understanding and extracting structured insights from unstructured documents remains a foundational challenge in industrial NLP. While Large Language Models (LLMs) …
arXiv:2603.00267v1 Announce Type: new Abstract: Misinformation spreading over the Internet poses a significant threat to both societies and individuals, necessitating robust and scalable fact-checking that …
arXiv:2603.00285v1 Announce Type: new Abstract: Evaluating AI agents in finance faces two key challenges: static benchmarks require costly expert annotation yet miss the dynamic decision-making …
arXiv:2603.00309v1 Announce Type: new Abstract: The increasingly popular agentic AI paradigm promises to harness the power of multiple, general-purpose large language model (LLM) agents to …
arXiv:2603.00349v1 Announce Type: new Abstract: Real-world scenarios increasingly require multiple embodied agents to collaborate in dynamic environments under embodied constraints, as many tasks exceed the …