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arXiv:2602.20973v1 Announce Type: new Abstract: To comprehensively evaluate the mathematical reasoning capabilities of Large Language Models (LLMs), researchers have introduced abundant mathematical reasoning datasets. However, …
arXiv:2602.20976v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly embedded in everyday decision-making, their safety responsibilities extend beyond reacting to explicit harmful …
arXiv:2602.21082v1 Announce Type: new Abstract: Customer-provided reviews have become an important source of information for business owners and other customers alike. However, effectively analyzing millions …
arXiv:2602.21103v1 Announce Type: new Abstract: Advanced reasoning typically requires Chain-of-Thought prompting, which is accurate but incurs prohibitive latency and substantial test-time inference costs. The standard …
arXiv:2602.21165v1 Announce Type: new Abstract: Patient-generated text such as secure messages, surveys, and interviews contains rich expressions of the patient voice (PV), reflecting communicative behaviors …
arXiv:2602.21193v1 Announce Type: new Abstract: Despite rapid recent progress in the terminal capabilities of large language models, the training data strategies behind state-of-the-art terminal agents …
arXiv:2602.20163v1 Announce Type: cross Abstract: Aphasia is an acquired language disorder caused by injury to the regions of the brain that are responsible for language. …
arXiv:2602.20191v1 Announce Type: cross Abstract: Changing runtime complexity on cloud and edge devices necessitates elastic large language model (LLM) deployment, where an LLM can be …
arXiv:2602.20224v1 Announce Type: cross Abstract: The rapid expansion of biomedical publications creates challenges for organizing knowledge and detecting emerging trends, underscoring the need for scalable …
arXiv:2602.20423v1 Announce Type: cross Abstract: Medical image segmentation remains challenging due to limited annotations for training, ambiguous anatomical features, and domain shifts. While vision-language models …
arXiv:2602.20449v1 Announce Type: cross Abstract: Modern Protein Language Models (PLMs) apply transformer-based model architectures from natural language processing to biological sequences, predicting a variety of …
arXiv:2602.20532v1 Announce Type: cross Abstract: Post-training large foundation models with reinforcement learning typically relies on massive and heterogeneous datasets, making effective curriculum learning both critical …