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- CelebA-Spoof: Large-Scale Face Anti-spoofing Dataset with Rich Annotations249
This work contributes a large-scale face anti-spoofing dataset, CelebA-Spoof, with the following appealing properties, and carefully benchmark existing methods in a unified multi-task framework, Auxiliary Information Embedding Network (AENet), and reveal several valuable observations.
- OASIS: Open Agent Social Interaction Simulations with One Million Agents161
OASIS is a generalizable and scalable social media simulator that replicates various social phenomena, including information spreading, group polarization, and herd effects across X and Reddit platforms, and demonstrates OASIS's potential as a powerful tool for studying complex systems in digital environments.
- SPA-VL: A Comprehensive Safety Preference Alignment Dataset for Vision Language Models95
SPA-VL, as a large-scale, high-quality, and diverse dataset, represents a significant milestone in ensuring that VLMs achieve both harmlessness and helpfulness.
- Many Heads Are Better Than One: Improved Scientific Idea Generation by A LLM-Based Multi-Agent System88
This work proposes an LLM-based multi-agent system, i.e., Virtual Scientists (VirSci), designed to mimic the teamwork inherent in scientific research, and investigates the collaboration mechanisms that contribute to its tendency to produce ideas with higher novelty.
- VLIPP: Towards Physically Plausible Video Generation with Vision and Language Informed Physical Prior57
A novel two-stage image-to-video generation framework that explicitly incorporates physics with vision and language informed physical prior and can produce physically plausible motion is proposed.
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- From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities26
This paper evaluates the closed-source GPT-4 and Gemini and 6 open-source LLMs and MLLMs and uncover 14 empirical findings that are useful to understand the capabilities and limitations of both proprietary and open-source MLLMs, towards more reliable downstream multi-modal applications.
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- VFXMaster: Unlocking Dynamic Visual Effect Generation via In-Context Learning12
VFXMaster is introduced, a unified, reference-based framework for VFX video generation that recasts effect generation as an in-context learning task, enabling it to reproduce diverse dynamic effects from a reference video onto target content and demonstrates remarkable generalization to unseen effect categories.
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- AI-Driven Automation Can Become the Foundation of Next-Era Science of Science Research5
A preliminary multi-agent system is presented as an illustrative example to simulate research societies, showcasing AI's ability to replicate real-world research patterns and accelerate progress in Science of Science research.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-13. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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