Alignment, bias, regulation, and responsible AI
![[2511.21331] The More, the Merrier: Contrastive Fusion for Higher-Order Multimodal Alignment](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Abstract page for arXiv paper 2511.21331: The More, the Merrier: Contrastive Fusion for Higher-Order Multimodal Alignment
Abstract page for arXiv paper 2509.22367: What Is The Political Content in LLMs' Pre- and Post-Training Data?
Abstract page for arXiv paper 2507.22264: SmartCLIP: Modular Vision-language Alignment with Identification Guarantees
The paper presents Guide-Guard, a machine learning solution designed to predict off-target effects in CRISPR applications with 84% accura...
This paper introduces a certification protocol for agent-to-agent communication in multiagent AI systems, addressing semantic drift and e...
This paper presents a Proxy State-Based Evaluation framework for assessing multi-turn tool-calling LLM agents, offering a scalable altern...
The paper presents SEMixer, a novel multiscale model designed for long-term time series forecasting, addressing challenges in modeling te...
This article benchmarks various uncertainty metrics for LLM-based automatic assessment, highlighting the challenges of output uncertainty...
This paper explores optimization instability in autonomous workflows for clinical symptom detection, revealing critical failure modes and...
The paper presents ModalImmune, a training framework designed to enhance the resilience of multimodal systems against input channel loss ...
This article presents a novel approach to enhance Physics-Informed Neural Networks (PINNs) by utilizing geometric compactification mappin...
This paper presents a novel approach to differentially private non-convex distributionally robust optimization (DRO), addressing challeng...
This paper explores the resilience of generative AI models against data contamination during recursive training, providing theoretical gu...
This article discusses a multi-objective alignment framework for language models aimed at enhancing personalized psychotherapy, balancing...
The paper proposes AI-CARE, a carbon-aware evaluation metric for machine learning models, addressing the environmental impact of model tr...
The paper presents BamaER, a memory-augmented model designed for personalized exercise recommendations based on students' learning behavi...
This article presents a framework for ensuring runtime stability and recovery in hybrid reasoning systems, emphasizing the importance of ...
This article discusses how personalization features in large language models (LLMs) can lead to sycophancy, where models overly agree wit...
A bipartisan movement is emerging across the U.S. to regulate AI in health insurance, challenging President Trump's push for less state o...
This article presents a philosophical dialogue on artificial consciousness, exploring the distinction between personhood and cognitive so...
Anthropic is in negotiations with the Pentagon over the use of its AI models, seeking assurances against their application in autonomous ...
The SDNY ruled that AI-generated documents using unsecured public tools are not protected by attorney-client privilege, emphasizing the r...
Scammers are exploiting AI by creating fake chatbots that impersonate Google's Gemini to sell a non-existent cryptocurrency called 'Googl...
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