Depth Gives a False Sense of Privacy: LLM Internal States Inversion
arXiv:2507.16372v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly integrated into daily routines, yet they raise significant privacy…
arXiv:2507.16372v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly integrated into daily routines, yet they raise significant privacy…
arXiv:2502.17163v4 Announce Type: replace-cross Abstract: Automatic evaluation of retrieval augmented generation (RAG) systems relies on fine-grained dimensions like faithfulness and…
arXiv:2507.15082v1 Announce Type: cross Abstract: We introduce a novel extension to robust control theory that explicitly addresses uncertainty in the…
arXiv:2507.14207v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) in K–12 education offers both transformative opportunities and…
arXiv:2507.14238v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly being used in user-facing applications, from providing medical consultations…
arXiv:2507.14000v2 Announce Type: replace-cross Abstract: This paper presents the Photonic FabricTM and the Photonic Fabric ApplianceTM (PFA), a photonic-enabled switch…
arXiv:2507.13511v1 Announce Type: new Abstract: Large Language Models (LLMs) offer significant promise for intelligent traffic management; however, current chain-based systems…
arXiv:2507.12871v2 Announce Type: replace-cross Abstract: Recently, there has been a surge of interest in Multi-Target Cross-Domain Recommendation (MTCDR), which aims…
arXiv:2507.13933v1 Announce Type: cross Abstract: Increasingly, web content is automatically generated by large language models (LLMs) with little human input.…
arXiv:2507.13941v1 Announce Type: cross Abstract: A fundamental question in cognitive neuroscience is what shapes visual perception: the external world’s structure…