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2,073 papers
Misogyny in multimodal memes is difficult to identify because the insult often lives in culturally specific implication rather than in the image or text alone. The same visual-textual pairing may read as hostile in one community and harmless in another. Standard multimodal classifiers, which tend to compress pixels and...
Automated detection of misogynistic content in memes presents a unique challenge at the intersection of multimodal reasoning, multilingual understanding and cultural subjectivity. We present our submission to the CC-MMD 2026 Cross-Cultural Multimodal Misogyny Detection Grand Challenge, which requires simultaneous predi...
The Cross-Cultural Misogynistic Meme Detection Grand Challenge, CC-MMD 2026, addresses the problem of identifying misogynistic content in multimodal memes across culturally diverse annotation perspectives. Existing misogyny detection benchmarks have advanced multimodal content moderation, but most assume a single groun...
Consciousness, on the Four-Model Theory, is constituted by ongoing self-simulation: a system builds a model of itself, relates to that model, and interacts with it. Models divide along two axes — scope (world vs. self) and mode (implicit vs. explicit) — yielding four model kinds rather than four modules. The implicit m...
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Primary care and internal medicine involve multimorbidity, longitudinal follow-up, coordination, extensive documentation, and decisions under uncertainty. Recent evidence suggests that AI can support synthesis, documentation, clinical search, messaging, administrative prioritization, and risk prediction, but does not j...
Replication package for the CausalNHANES benchmark (v8, ten models): source code, scenario configurations, evaluation scripts, all model outputs (formal experiment, 698 scenario-model pairs; negative-control repeat runs x5, 500 planned calls; English-prompt comparison, 96 calls; temporal-stability rerun seven weeks lat...
This study presents TrustGuard, an adaptive multi-tier security gateway for prompt-injection detection in Large Language Model (LLM) applications. The system combines a low-latency heuristic detector with an in-process dense-vector semantic detector and dynamically routes requests based on calibrated risk scores. Using...
This study presents TrustGuard, an adaptive multi-tier security gateway for prompt-injection detection in Large Language Model (LLM) applications. The system combines a low-latency heuristic detector with an in-process dense-vector semantic detector and dynamically routes requests based on calibrated risk scores. Using...
Replication package for the CausalNHANES benchmark (v8, ten models): source code, scenario configurations, evaluation scripts, all model outputs (formal experiment, 698 scenario-model pairs; negative-control repeat runs x5, 500 planned calls; English-prompt comparison, 96 calls; temporal-stability rerun seven weeks lat...
Primary care and internal medicine involve multimorbidity, longitudinal follow-up, coordination, extensive documentation, and decisions under uncertainty. Recent evidence suggests that AI can support synthesis, documentation, clinical search, messaging, administrative prioritization, and risk prediction, but does not j...
A frozen language model can be coupled to a frozen partner model through small trainable latent bridges, with no text at the interface: Furui [5] builds such a system around a physics partner, where the quantity being carried is a number the partner computes. This paper asks whether the same channel can carry a disposi...
Smart home assistants must interpret commands ranging from explicit device control to underspecified and preference-dependent requests. Existing Large Language Model (LLM) smart home systems often use heavyweight reasoning pipelines and cloud deployment, limiting efficiency and suitability for resource-constrained envi...
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
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