A survey of LLM copyright protection that unifies text watermarking, model watermarking, and model fingerprinting while presenting new coverage of fingerprint transfer and removal.
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Fine-tuning 13 CodeLMs on a constructed CLB dataset with nine interaction types improves detection, with UniXcoder-base reaching F1 0.7407 and small models outperforming large ones.
ToxiShield delivers a real-time GitHub extension with a BERT toxicity detector at 98% accuracy, a Claude-based coach, and a fine-tuned Llama reframer at 95% style transfer accuracy, validated by a 10-person TAM study.
The survey organizes causes of hallucinations in MLLMs, reviews evaluation benchmarks and metrics, and outlines mitigation approaches plus open questions.
The paper introduces a new taxonomy for model merging methods and reviews their applications in LLMs, MLLMs, continual learning, multi-task learning, and other subfields while outlining open challenges.
A systematic literature review that organizes recent work on LLMs for code generation into a taxonomy covering data curation, model advances, evaluations, ethics, environmental impact, and applications, with benchmark comparisons.
The paper surveys data-centric strategies for foundation models in computational healthcare and supplies a curated list of related models and datasets.
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Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends
A survey of LLM copyright protection that unifies text watermarking, model watermarking, and model fingerprinting while presenting new coverage of fingerprint transfer and removal.
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Fine-Tuning Code Language Models to Detect Cross-Language Bugs
Fine-tuning 13 CodeLMs on a constructed CLB dataset with nine interaction types improves detection, with UniXcoder-base reaching F1 0.7407 and small models outperforming large ones.
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ToxiShield: Promoting Inclusive Developer Communication through Real-Time Toxicity Filtering
ToxiShield delivers a real-time GitHub extension with a BERT toxicity detector at 98% accuracy, a Claude-based coach, and a fine-tuned Llama reframer at 95% style transfer accuracy, validated by a 10-person TAM study.
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Hallucination of Multimodal Large Language Models: A Survey
The survey organizes causes of hallucinations in MLLMs, reviews evaluation benchmarks and metrics, and outlines mitigation approaches plus open questions.
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Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities
The paper introduces a new taxonomy for model merging methods and reviews their applications in LLMs, MLLMs, continual learning, multi-task learning, and other subfields while outlining open challenges.
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A Survey on Large Language Models for Code Generation
A systematic literature review that organizes recent work on LLMs for code generation into a taxonomy covering data curation, model advances, evaluations, ethics, environmental impact, and applications, with benchmark comparisons.
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Data-Centric Foundation Models in Computational Healthcare: A Survey
The paper surveys data-centric strategies for foundation models in computational healthcare and supplies a curated list of related models and datasets.