Find the idea.
Understand the evidence.
Research perspectives and practical workflow proposals across industries. Explore what has been studied, what is still uncertain, and how to test a useful first project.
Before you build an agent team, define one good workflow.
A practical way to choose between fixed workflows, tool-using agents, and specialist teams—starting with a decision your business can actually verify.
Read the perspectiveAgent architecture
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Operations blueprint
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Procurement agents should build the evidence before the shortlist.
How to turn quotes, delivery constraints and approval policies into a traceable comparison—without letting a model invent the winning supplier.
A healthcare scheduling agent needs a state machine, not a promise.
A careful administrative blueprint for proposed appointments, resource checks and staff confirmation, grounded in the FHIR scheduling model.
Commerce agents have to respect inventory truth.
Why available stock, reserved units and location matter more than a convincing sales reply—and how to design an exception workflow around them.
Let a solver plan routes. Let an agent explain the exceptions.
A logistics blueprint that separates constraint solving from conversational coordination, so proposed plans remain feasible and inspectable.
Research to practice
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From language to robot action: the boundary that matters.
What OpenVLA shows about learned robot policies, and why a first business pilot should separate task planning from physical execution.
Research agents should make hypotheses easier to challenge.
What Co-Scientist and ChemCrow suggest about tool-assisted research, and a proposed evidence workflow that preserves uncertainty and expert review.
Connected systems
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From the analysis archive
AI-generated / not independently verified
These earlier AI-generated analyses remain available for exploration. Their claims, citations, market estimates and implementation proposals have not been independently verified. Check the original sources before relying on them.
Fast3Dcache: Training-free 3D Geometry Synthesis Acceleration: Analysis of Fast3Dcache: Training-free 3D Geometry Synthesis Acceleration
Diffusion models have achieved impressive generative quality across modalities like 2D images, videos, and 3D shapes, but their inference remains computationally expensive due to the iterative denoisi...
SAM 3: Segment Anything with Concepts
We present Segment Anything Model (SAM) 3, a unified model that detects, segments, and tracks objects in images and videos based on concept prompts, which we define as either short noun phrases (e.g., "yellow school bus"), image exemplars,…
LiveAvatar: Analysis of Alibaba-Quark/LiveAvatar
Implementation of "Live Avatar: Streaming Real-time Audio-Driven Avatar Generation with Infinite Length"
dKV-Cache: The Cache for Diffusion Language Models: Analysis of dKV-Cache: The Cache for Diffusion Language Models
Diffusion Language Models (DLMs) have been seen as a promising competitor for autoregressive language models. However, diffusion language models have long been constrained by slow inference. A core ch...
Foundations of GenIR: Analysis of Foundations of GenIR
The chapter discusses the foundational impact of modern generative AI models on information access (IA) systems. In contrast to traditional AI, the large-scale training and superior data modeling of g...
What does it mean to understand language?: Analysis of What does it mean to understand language?
Language understanding entails not just extracting the surface-level meaning of the linguistic input, but constructing rich mental models of the situation it describes. Here we propose that because pr...
When AI Takes the Couch: Psychometric Jailbreaks Reveal Internal Conflict in Frontier Models
Frontier large language models (LLMs) such as ChatGPT, Grok and Gemini are increasingly used for mental-health support with anxiety, trauma and self-worth. Most work treats them as tools or as targets of personality tests, assuming they…
AutoNeural: Co-Designing Vision-Language Models for NPU Inference
While Neural Processing Units (NPUs) offer high theoretical efficiency for edge AI, state-of-the-art Vision--Language Models (VLMs) tailored for GPUs often falter on these substrates. We attribute this hardware-model mismatch to two…
DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models
We introduce DeepSeek-V3.2, a model that harmonizes high computational efficiency with superior reasoning and agent performance. The key technical breakthroughs of DeepSeek-V3.2 are as follows: (1) DeepSeek Sparse Attention (DSA): We…
Structured Extraction from Business Process Diagrams Using Vision-Language Models
Business Process Model and Notation (BPMN) is a widely adopted standard for representing complex business workflows. While BPMN diagrams are often exchanged as visual images, existing methods primarily rely on XML representations for…
Recognition of Abnormal Events in Surveillance Videos using Weakly Supervised Dual-Encoder Models
We address the challenge of detecting rare and diverse anomalies in surveillance videos using only video-level supervision. Our dual-backbone framework combines convolutional and transformer representations through top-k pooling, achieving…
Vanishing Bias Heuristic-guided Reinforcement Learning Algorithm: Analysis of Vanishing Bias Heuristic-guided Reinforcement Learning Algorithm
Reinforcement Learning has achieved tremendous success in the many Atari games. In this paper we explored with the lunar lander environment and implemented classical methods including Q-Learning, SARSA, MC as well as tiling coding. We also…
OmniRefiner: Reinforcement-Guided Local Diffusion Refinement
Reference-guided image generation has progressed rapidly, yet current diffusion models still struggle to preserve fine-grained visual details when refining a generated image using a reference. This limitation arises because VAE-based…
Generative World Modelling for Humanoids: 1X World Model Challenge Technical Report: Analysis of Generative World Modelling for Humanoids: 1X World Model Challenge Technical Report
World models are a powerful paradigm in AI and robotics, enabling agents to reason about the future by predicting visual observations or compact latent states. The 1X World Model Challenge introduces an open-source benchmark of real-world…
Decoupled DMD: CFG Augmentation as the Spear, Distribution Matching as the Shield
Diffusion model distillation has emerged as a powerful technique for creating efficient few-step and single-step generators. Among these, Distribution Matching Distillation (DMD) and its variants stand out for their impressive performance,…
Fast3Dcache: Training-free 3D Geometry Synthesis Acceleration
Diffusion models have achieved impressive generative quality across modalities like 2D images, videos, and 3D shapes, but their inference remains computationally expensive due to the iterative denoising process. While recent caching-based…
YOLO Meets Mixture-of-Experts: Adaptive Expert Routing for Robust Object Detection
A Mixture-of-Experts framework with adaptive routing among multiple YOLOv9-T experts improves object detection performance by achieving higher mAP and AR.
Find the Leak, Fix the Split: Cluster-Based Method to Prevent Leakage in Video-Derived Datasets
A cluster-based frame selection strategy groups visually similar frames to create more representative and balanced dataset partitions, reducing information leakage in video-derived frames datasets.