Ai Safety
Newsom signs executive order requiring AI companies to have safety, privacy guardrails
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Reddit - Artificial Intelligence
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1 min
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AI Safety & Ethics
Alignment, bias, regulation, and responsible AI
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![[2511.16417] Pharos-ESG: A Framework for Multimodal Parsing, Contextual Narration, and Hierarchical Labeling of ESG Report](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Ai Safety
[2511.16417] Pharos-ESG: A Framework for Multimodal Parsing, Contextual Narration, and Hierarchical Labeling of ESG Report
Abstract page for arXiv paper 2511.16417: Pharos-ESG: A Framework for Multimodal Parsing, Contextual Narration, and Hierarchical Labeling...
arXiv - AI
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4 min
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Llms
[2510.08847] What Is Your Agent's GPA? A Framework for Evaluating Agent Goal-Plan-Action Alignment
Abstract page for arXiv paper 2510.08847: What Is Your Agent's GPA? A Framework for Evaluating Agent Goal-Plan-Action Alignment
arXiv - AI
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4 min
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All Content
Machine Learning
[2410.12439] Beyond Attribution: Unified Concept-Level Explanations
The paper presents UnCLE, a framework that enhances model-agnostic explanation techniques by integrating concept-based approaches, offeri...
arXiv - Machine Learning
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3 min
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Machine Learning
[2602.22935] A Holistic Framework for Robust Bangla ASR and Speaker Diarization with Optimized VAD and CTC Alignment
This paper presents a robust framework for Bangla Automatic Speech Recognition (ASR) and Speaker Diarization, addressing challenges in pr...
arXiv - AI
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3 min
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Machine Learning
[2410.10922] Towards Privacy-Guaranteed Label Unlearning in Vertical Federated Learning: Few-Shot Forgetting without Disclosure
This paper introduces a novel method for label unlearning in Vertical Federated Learning (VFL), addressing privacy concerns while maintai...
arXiv - Machine Learning
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4 min
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Machine Learning
[2404.01877] Procedural Fairness in Machine Learning
This paper explores procedural fairness in machine learning, proposing a new metric for evaluation and methods to enhance fairness withou...
arXiv - Machine Learning
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4 min
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Machine Learning
[2602.23192] FairQuant: Fairness-Aware Mixed-Precision Quantization for Medical Image Classification
The paper presents FairQuant, a framework for fairness-aware mixed-precision quantization in medical image classification, optimizing bot...
arXiv - Machine Learning
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3 min
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Llms
[2602.22790] Natural Language Declarative Prompting (NLD-P): A Modular Governance Method for Prompt Design Under Model Drift
The paper introduces Natural Language Declarative Prompting (NLD-P), a governance method for prompt design that addresses challenges pose...
arXiv - AI
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4 min
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Ai Startups
[2602.22775] TherapyProbe: Generating Design Knowledge for Relational Safety in Mental Health Chatbots Through Adversarial Simulation
The paper introduces TherapyProbe, a methodology for enhancing relational safety in mental health chatbots through adversarial simulation...
arXiv - AI
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3 min
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Machine Learning
[2602.23085] Q-Tag: Watermarking Quantum Circuit Generative Models
The paper presents Q-Tag, a novel watermarking framework for quantum circuit generative models (QCGMs), addressing the need for secure co...
arXiv - Machine Learning
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4 min
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Llms
[2602.23079] Assessing Deanonymization Risks with Stylometry-Assisted LLM Agent
This article introduces a novel LLM agent designed to assess and mitigate deanonymization risks in textual data using a method called SAL...
arXiv - Machine Learning
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3 min
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Machine Learning
[2602.22740] AMLRIS: Alignment-aware Masked Learning for Referring Image Segmentation
The paper presents AMLRIS, a novel training strategy for Referring Image Segmentation (RIS) that enhances object segmentation through ali...
arXiv - AI
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3 min
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Llms
[2602.22724] AgentSentry: Mitigating Indirect Prompt Injection in LLM Agents via Temporal Causal Diagnostics and Context Purification
AgentSentry introduces a novel framework to mitigate indirect prompt injection (IPI) in LLM agents, enhancing their security while mainta...
arXiv - AI
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4 min
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Ai Safety
[2602.22710] Same Words, Different Judgments: Modality Effects on Preference Alignment
This study explores how modality affects preference alignment in AI systems, comparing human and synthetic evaluations of audio and text ...
arXiv - AI
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3 min
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Llms
[2602.22700] IMMACULATE: A Practical LLM Auditing Framework via Verifiable Computation
The paper presents IMMACULATE, a framework for auditing large language models (LLMs) using verifiable computation to detect economic devi...
arXiv - AI
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3 min
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Llms
[2602.22903] PSQE: A Theoretical-Practical Approach to Pseudo Seed Quality Enhancement for Unsupervised MMEA
The paper presents PSQE, a method for enhancing pseudo seed quality in unsupervised multimodal entity alignment, addressing challenges in...
arXiv - Machine Learning
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4 min
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Computer Vision
[2602.22621] CGSA: Class-Guided Slot-Aware Adaptation for Source-Free Object Detection
The paper presents CGSA, a novel framework for Source-Free Domain Adaptive Object Detection that integrates object-centric learning to en...
arXiv - AI
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3 min
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Machine Learning
[2602.22699] DPSQL+: A Differentially Private SQL Library with a Minimum Frequency Rule
DPSQL+ is a new SQL library designed to enhance data privacy by enforcing differential privacy and a minimum frequency rule, ensuring sen...
arXiv - Machine Learning
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4 min
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Machine Learning
[2602.22570] Guidance Matters: Rethinking the Evaluation Pitfall for Text-to-Image Generation
The paper discusses the evaluation challenges in text-to-image generation, focusing on classifier-free guidance (CFG) and proposing a new...
arXiv - AI
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4 min
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Machine Learning
[2602.22631] TorchLean: Formalizing Neural Networks in Lean
TorchLean is a framework that formalizes neural networks within the Lean 4 theorem prover, enabling precise semantics for execution and v...
arXiv - Machine Learning
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4 min
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Llms
[2602.22564] Addressing Climate Action Misperceptions with Generative AI
This study explores how a personalized large language model (LLM) can correct climate action misperceptions among climate-concerned indiv...
arXiv - AI
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3 min
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Machine Learning
[2602.22609] EvolveGen: Algorithmic Level Hardware Model Checking Benchmark Generation through Reinforcement Learning
EvolveGen introduces a novel framework for generating hardware model checking benchmarks using reinforcement learning, addressing the ben...
arXiv - Machine Learning
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4 min
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