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arXiv:2409.08846v3 Announce Type: replace-cross Abstract: Backdoor-based fingerprinting has emerged as an effective technique for tracing the ownership of large language...
arXiv:2508.18370v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated exceptional capabilities when trained within executable runtime environments, notably...
arXiv:2508.17623v2 Announce Type: replace Abstract: Speech emotions play a crucial role in human-computer interaction, shaping engagement and context-aware communication. Despite...
arXiv:2408.05873v3 Announce Type: replace Abstract: Large language models (LLMs) have shown remarkable performance in various tasks but often fail to...
arXiv:2508.18387v1 Announce Type: new Abstract: Softmax self-attention often assigns disproportionate weight to semantically uninformative tokens such as special tokens and...
arXiv:2508.08243v3 Announce Type: replace Abstract: Unlimited, or so-called helpful-only language models are trained without safety alignment constraints and never refuse...
arXiv:2508.17536v1 Announce Type: new Abstract: Multi-Agent Debate~(MAD) has emerged as a promising paradigm for improving the performance of large language...
arXiv:2508.17184v1 Announce Type: new Abstract: Instruction tuning is a pivotal technique for aligning large language models (LLMs) with human intentions,...
arXiv:2508.18245v1 Announce Type: new Abstract: The use of Large Language Models (LLMs) has proven to be a tool that could...




