Generative AI

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The Real Reason OpenAI Shut Sora Down Is a Warning to Every AI Startup

Really, you made this without AI? Prove it | The Verge

Creatives want to start labeling human-made text, images, audio, and video with AI-free logos. Now they just have to pick one.

[2412.18899] GAI: Generative Agents for Innovation

The paper explores GAI, a framework for generative agents that enhances collective reasoning to foster innovation, evaluated through a ca...

[2602.17664] Sink-Aware Pruning for Diffusion Language Models

The paper presents Sink-Aware Pruning, a novel method for optimizing Diffusion Language Models (DLMs) by identifying and removing unstabl...

[2602.17598] The Cascade Equivalence Hypothesis: When Do Speech LLMs Behave Like ASR$\rightarrow$LLM Pipelines?

The paper explores the Cascade Equivalence Hypothesis, examining when speech LLMs function similarly to ASR→LLM pipelines. It highlights ...

[2602.17450] Beyond Pipelines: A Fundamental Study on the Rise of Generative-Retrieval Architectures in Web Research

This paper explores the evolution of web research through generative-retrieval architectures, highlighting the transformative impact of l...

[2602.17431] Fine-Grained Uncertainty Quantification for Long-Form Language Model Outputs: A Comparative Study

This study presents a taxonomy for fine-grained uncertainty quantification in long-form language model outputs, highlighting effective me...

[2602.17185] The Bots of Persuasion: Examining How Conversational Agents' Linguistic Expressions of Personality Affect User Perceptions and Decisions

This article explores how the linguistic expressions of personality in conversational agents (CAs) influence user perceptions and decisio...

[2602.17133] VP-VAE: Rethinking Vector Quantization via Adaptive Vector Perturbation

The paper introduces VP-VAE, a novel approach to Vector Quantized Variational Autoencoders that decouples representation learning from di...

[2602.16968] DDiT: Dynamic Patch Scheduling for Efficient Diffusion Transformers

The paper presents DDiT, a novel approach for dynamic patch scheduling in diffusion transformers, enhancing efficiency in image and video...

[2602.16930] Say It My Way: Exploring Control in Conversational Visual Question Answering with Blind Users

The paper explores how blind users can customize interactions with conversational visual question answering systems, highlighting the nee...

[2602.16928] Discovering Multiagent Learning Algorithms with Large Language Models

This paper explores the use of large language models to automatically discover new multiagent learning algorithms, enhancing the efficien...

[2602.16873] AdaptOrch: Task-Adaptive Multi-Agent Orchestration in the Era of LLM Performance Convergence

The paper presents AdaptOrch, a framework for task-adaptive multi-agent orchestration that enhances performance by optimizing orchestrati...

[2602.16820] AI-Mediated Feedback Improves Student Revisions: A Randomized Trial with FeedbackWriter in a Large Undergraduate Course

This study investigates the effectiveness of AI-mediated feedback on student revisions in a large undergraduate course, revealing that AI...

[2602.16813] One-step Language Modeling via Continuous Denoising

The paper presents a novel flow-based language model (FLM) that utilizes continuous denoising to achieve superior generation quality and ...

[2602.16729] Intent Laundering: AI Safety Datasets Are Not What They Seem

The paper evaluates AI safety datasets, revealing they often misrepresent real-world attacks due to an overreliance on triggering cues, l...

[2602.17602] MolHIT: Advancing Molecular-Graph Generation with Hierarchical Discrete Diffusion Models

MolHIT introduces a novel framework for molecular graph generation using Hierarchical Discrete Diffusion Models, achieving state-of-the-a...

[2602.17560] ODESteer: A Unified ODE-Based Steering Framework for LLM Alignment

The paper presents ODESteer, a novel ODE-based framework for aligning large language models (LLMs) by addressing limitations in existing ...

[2602.17529] Enhancing Large Language Models (LLMs) for Telecom using Dynamic Knowledge Graphs and Explainable Retrieval-Augmented Generation

This article presents a novel framework, KG-RAG, that enhances large language models (LLMs) for telecom applications by integrating dynam...

[2602.17418] A Privacy by Design Framework for Large Language Model-Based Applications for Children

This article proposes a Privacy by Design framework for AI applications targeting children, addressing privacy risks and compliance with ...

[2602.17221] From Labor to Collaboration: A Methodological Experiment Using AI Agents to Augment Research Perspectives in Taiwan's Humanities and Social Sciences

This article explores a methodological experiment using AI agents to enhance research in Taiwan's humanities and social sciences, proposi...

[2602.17116] Epistemology of Generative AI: The Geometry of Knowing

This article explores the epistemological implications of generative AI, proposing a new framework for understanding knowledge production...