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.
StereoWorld: Geometry-Aware Monocular-to-Stereo Video Generation
The growing adoption of XR devices has fueled strong demand for high-quality stereo video, yet its production remains costly and artifact-prone. To address this challenge, we present StereoWorld, an end-to-end framework that repurposes a…
Gradient-Based Discovery: Architecting the High-Performance Computational Core for AI Co-Scientists
Powerful automatic differentiation in C++ and Python
Wan-Move: Motion-controllable Video Generation via Latent Trajectory Guidance
We present Wan-Move, a simple and scalable framework that brings motion control to video generative models. Existing motion-controllable methods typically suffer from coarse control granularity and limited scalability, leaving their…
Unified Video Editing with Temporal Reasoner
Existing video editing methods face a critical trade-off: expert models offer precision but rely on task-specific priors like masks, hindering unification; conversely, unified temporal in-context learning models are mask-free but lack…
RealGen: Photorealistic Text-to-Image Generation via Detector-Guided Rewards
With the continuous advancement of image generation technology, advanced models such as GPT-Image-1 and Qwen-Image have achieved remarkable text-to-image consistency and world knowledge However, these models still fall short in…
Relational Visual Similarity
Humans do not just see attribute similarity -- we also see relational similarity. An apple is like a peach because both are reddish fruit, but the Earth is also like a peach: its crust, mantle, and core correspond to the peach's skin,…
1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities
Scaling up self-supervised learning has driven breakthroughs in language and vision, yet comparable progress has remained elusive in reinforcement learning (RL). In this paper, we study building block...
Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free
Gating mechanisms have been widely utilized, from early models like LSTMs and Highway Networks to recent state space models, linear attention, and also softmax attention. Yet, existing literature rare...
Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond)
Language models (LMs) often struggle to generate diverse, human-like creative content, raising concerns about the long-term homogenization of human thought through repeated exposure to similar outputs...
EditThinker: Unlocking Iterative Reasoning for Any Image Editor
Instruction-based image editing has emerged as a prominent research area, which, benefiting from image generation foundation models, have achieved high aesthetic quality, making instruction-following capability the primary challenge.…
Live Avatar: Streaming Real-time Audio-Driven Avatar Generation with Infinite Length
Existing diffusion-based video generation methods are fundamentally constrained by sequential computation and long-horizon inconsistency, limiting their practical adoption in real-time, streaming audio-driven avatar synthesis. We present…
Titans: Learning to Memorize at Test Time
Over more than a decade there has been an extensive research effort on how to effectively utilize recurrent models and attention. While recurrent models aim to compress the data into a fixed-size memo...
It's All Connected: A Journey Through Test-Time Memorization, Attentional Bias, Retention, and Online Optimization
Designing efficient and effective architectural backbones has been in the core of research efforts to enhance the capability of foundation models. Inspired by the human cognitive phenomenon of attenti...
The Cell Ontology in the age of single-cell omics: Analysis of The Cell Ontology in the age of single-cell omics
Single-cell omics technologies have transformed our understanding of cellular diversity by enabling high-resolution profiling of individual cells. However, the unprecedented scale and heterogeneity of...
Thinking with Video: Video Generation as a Promising Multimodal Reasoning Paradigm
"Thinking with Text" and "Thinking with Images" paradigm significantly improve the reasoning ability of large language models (LLMs) and Vision Language Models (VLMs). However, these paradigms have in...
SignRoundV2: Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs
Extreme low-bit quantization is critical for efficiently deploying Large Language Models (LLMs), yet it often leads to severe performance degradation at 2-bits and even 4-bits (e.g., MXFP4). We present SignRoundV2, a post-training…
Qwen3-VL Technical Report
We introduce Qwen3-VL, the most capable vision-language model in the Qwen series to date, achieving superior performance across a broad range of multimodal benchmarks. It natively supports interleaved contexts of up to 256K tokens,…
A Multi-Modal AI Copilot for Single-Cell Analysis with Instruction Following
Large language models excel at interpreting complex natural language instructions, enabling them to perform a wide range of tasks. In the life sciences, single-cell RNA sequencing (scRNA-seq) data ser...
From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery
Artificial intelligence (AI) is reshaping scientific discovery, evolving from specialized computational tools into autonomous research partners. We position Agentic Science as a pivotal stage within t...
Semantics Lead the Way: Harmonizing Semantic and Texture Modeling with Asynchronous Latent Diffusion
Latent Diffusion Models (LDMs) inherently follow a coarse-to-fine generation process, where high-level semantic structure is generated slightly earlier than fine-grained texture. This indicates the preceding semantics potentially benefit…
ENACT: Evaluating Embodied Cognition with World Modeling of Egocentric Interaction: Analysis of ENACT: Evaluating Embodied Cognition with World Modeling of Egocentric Interaction
Embodied cognition argues that intelligence arises from sensorimotor interaction rather than passive observation. It raises an intriguing question: do modern vision-language models (VLMs), trained lar...
Invasive species, extreme fire risk, and toxin release under a changing climate: Analysis of Invasive species, extreme fire risk, and toxin release under a changing climate
Mediterranean ecosystems such as those found in California, Central Chile, Southern Europe, and Southwest Australia host numerous, diverse, fire-adapted micro-ecosystems. These micro-ecosystems are as...
DAComp: Benchmarking Data Agents across the Full Data Intelligence Lifecycle
Real-world enterprise data intelligence workflows encompass data engineering that turns raw sources into analytical-ready tables and data analysis that convert those tables into decision-oriented insights. We introduce DAComp, a benchmark…
Byzantine-Resilient SGD in High Dimensions on Heterogeneous Data
We study distributed stochastic gradient descent (SGD) in the master-worker architecture under Byzantine attacks. We consider the heterogeneous data model, where different workers may have different l...