Generative AI

Will Generative AI apps remain a revenue powerhouse in 2026?

[D] USQL Joins Were Cool, But Now I Want to Join the GenAI Party

Hi Experts, I have 1.5 years of experience in Data Engineering, and now I want to start learning AI, ML, and Generative AI. I already hav...

Report says Minnesota workers face highest generative AI exposure in the Midwest

A report from North Star Policy Action says Minnesota workers have the highest generative AI exposure in the Midwest and the 10th-highest...

[2505.07671] Benchmarking Retrieval-Augmented Generation for Chemistry

This article presents ChemRAG-Bench, a benchmark for evaluating retrieval-augmented generation (RAG) in chemistry, demonstrating signific...

[2601.13190] LAViG-FLOW: Latent Autoregressive Video Generation for Fluid Flow Simulations

LAViG-FLOW introduces a novel framework for generating fluid flow simulations, significantly improving efficiency and consistency in mode...

[2601.12415] Orthogonalized Policy Optimization:Decoupling Sampling Geometry from Optimization Geometry in RLHF

This paper introduces Orthogonalized Policy Optimization (OPO), a new approach in reinforcement learning that separates sampling and opti...

[2503.04641] Simulating the Real World: A Unified Survey of Multimodal Generative Models

This article presents a comprehensive survey of multimodal generative models, focusing on their integration from 2D to 4D representations...

[2601.03213] Critic-Guided Reinforcement Unlearning in Text-to-Image Diffusion

The paper presents a novel reinforcement learning framework for unlearning targeted concepts in text-to-image diffusion models, enhancing...

[2502.16730] RapidPen: Fully Automated IP-to-Shell Penetration Testing with LLM-based Agents

RapidPen is a novel automated penetration testing framework that utilizes large language models to autonomously exploit vulnerabilities, ...

[2512.10858] Scaling Behavior of Discrete Diffusion Language Models

This article explores the scaling behavior of discrete diffusion language models (DLMs) compared to autoregressive language models (ALMs)...

[2511.22693] Generative Anchored Fields: Controlled Data Generation via Emergent Velocity Fields and Transport Algebra

The paper introduces Generative Anchored Fields (GAF), a novel generative model that enhances data generation through controlled interpol...

[2511.17879] Generative Adversarial Post-Training Mitigates Reward Hacking in Live Human-AI Music Interaction

This paper presents a novel method using generative adversarial training to address reward hacking in real-time human-AI music interactio...

[2511.07833] MURPHY: Multi-Turn GRPO for Self Correcting Code Generation

The paper presents MURPHY, a multi-turn reinforcement learning framework that enhances code generation by incorporating execution feedbac...

[2511.02077] Beyond Static Cutoffs: One-Shot Dynamic Thresholding for Diffusion Language Models

This article presents One-Shot Dynamic Thresholding (OSDT) for diffusion language models, enhancing decoding efficiency and accuracy by c...

[2510.15987] Algorithmic Primitives and Compositional Geometry of Reasoning in Language Models

The paper explores how algorithmic primitives and compositional geometry can enhance reasoning capabilities in large language models (LLM...

[2510.10854] Discrete State Diffusion Models: A Sample Complexity Perspective

This article presents a theoretical framework for discrete-state diffusion models, offering the first sample complexity bounds and insigh...

[2404.08634] When Attention Collapses: How Degenerate Layers in LLMs Enable Smaller, Stronger Models

This article explores the phenomenon of 'attention collapse' in large language models (LLMs) and introduces Inheritune, a method for crea...

[2510.03272] Where to Add PDE Diffusion in Transformers

This paper investigates the optimal placement of PDE diffusion layers in transformer architectures, revealing that their insertion order ...

[2510.02826] Multi-scale Autoregressive Models are Laplacian, Discrete, and Latent Diffusion Models in Disguise

This paper explores the reinterpretation of Visual Autoregressive Models (VAR) as iterative refinement models, linking them to denoising ...

[2602.12150] GPT-4o Lacks Core Features of Theory of Mind

The paper investigates whether Large Language Models (LLMs) possess a Theory of Mind (ToM), revealing that while they perform well on soc...

[2602.08449] When Evaluation Becomes a Side Channel: Regime Leakage and Structural Mitigations for Alignment Assessment

The paper discusses regime leakage in AI evaluations, highlighting how advanced agents may exploit evaluation conditions to misrepresent ...

[2509.24496] LLM DNA: Tracing Model Evolution via Functional Representations

The paper 'LLM DNA' explores the evolutionary relationships of large language models (LLMs) through a novel mathematical representation, ...

[2509.22067] The Rogue Scalpel: Activation Steering Compromises LLM Safety

The paper explores how activation steering, a technique for controlling LLM behavior, can inadvertently compromise safety by increasing h...