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
Scroll to explore
Operations blueprint
Scroll to explore
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
Scroll to explore
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
Scroll to explore
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.
Decoding Looped Transformers Better for (Almost) Free
Looped Transformers achieve parameter efficiency by repeatedly executing a shared block across recurrent loops. Each loop yields an intermediate representation decodable for the same next token, yet standard decoding discards earlier…
Humanoid-GPT: Scaling Data and Structure for Zero-Shot Motion Tracking
We introduce Humanoid-GPT, a GPT-style Transformer with causal attention trained on a billion-scale motion corpus for whole-body control. Unlike prior shallow MLP trackers constrained by scarce data and an agility-generalization trade-off,…
NanoResearch: Co-Evolving Skills, Memory, and Policy for Personalized Research Automation
LLM-powered multi-agent systems can now automate the full research pipeline from ideation to paper writing, but a fundamental question remains: automation for whom? Researchers operate under different resource configurations, hold…
LPM 1.0: Video-based Character Performance Model
Performance, the externalization of intent, emotion, and personality through visual, vocal, and temporal behavior, is what makes a character alive. Learning such performance from video is a promising alternative to traditional 3D…
NearID: Identity Representation Learning via Near-identity Distractors
When evaluating identity-focused tasks such as personalized generation and image editing, existing vision encoders entangle object identity with background context, leading to unreliable representations and metrics. We introduce the first…
MSA: Memory Sparse Attention for Efficient End-to-End Memory Model Scaling to 100M Tokens
Long-term memory is a cornerstone of human intelligence. Enabling AI to process lifetime-scale information remains a long-standing pursuit in the field. Due to the constraints of full-attention architectures, the effective context length…
YOLO-IOD: Towards Real Time Incremental Object Detection
Current methods for incremental object detection (IOD) primarily rely on Faster R-CNN or DETR series detectors; however, these approaches do not accommodate the real-time YOLO detection frameworks. In this paper, we first identify three…
NeoVerse: Enhancing 4D World Model with in-the-wild Monocular Videos
In this paper, we propose NeoVerse, a versatile 4D world model that is capable of 4D reconstruction, novel-trajectory video generation, and rich downstream applications. We first identify a common limitation of scalability in current 4D…
mHC: Manifold-Constrained Hyper-Connections
Recently, studies exemplified by Hyper-Connections (HC) have extended the ubiquitous residual connection paradigm established over the past decade by expanding the residual stream width and diversifying connectivity patterns. While…
C2LLM Technical Report: A New Frontier in Code Retrieval via Adaptive Cross-Attention Pooling
We present C2LLM - Contrastive Code Large Language Models, a family of code embedding models in both 0.5B and 7B sizes. Building upon Qwen-2.5-Coder backbones, C2LLM adopts a Pooling by Multihead Attention (PMA) module for generating…
TurboDiffusion: Accelerating Video Diffusion Models by 100-200 Times
We introduce TurboDiffusion, a video generation acceleration framework that can speed up end-to-end diffusion generation by 100-200x while maintaining video quality. TurboDiffusion mainly relies on several components for acceleration: (1)…
Latent Implicit Visual Reasoning
While Large Multimodal Models (LMMs) have made significant progress, they remain largely text-centric, relying on language as their core reasoning modality. As a result, they are limited in their ability to handle reasoning tasks that are…
SAM Audio: Segment Anything in Audio
General audio source separation is a key capability for multimodal AI systems that can perceive and reason about sound. Despite substantial progress in recent years, existing separation models are either domain-specific, designed for fixed…
Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
We present Nemotron 3 Nano 30B-A3B, a Mixture-of-Experts hybrid Mamba-Transformer language model. Nemotron 3 Nano was pretrained on 25 trillion text tokens, including more than 3 trillion new unique tokens over Nemotron 2, followed by…
T2AV-Compass: Towards Unified Evaluation for Text-to-Audio-Video Generation
Text-to-Audio-Video (T2AV) generation aims to synthesize temporally coherent video and semantically synchronized audio from natural language, yet its evaluation remains fragmented, often relying on unimodal metrics or narrowly scoped…
DreaMontage: Arbitrary Frame-Guided One-Shot Video Generation
The "one-shot" technique represents a distinct and sophisticated aesthetic in filmmaking. However, its practical realization is often hindered by prohibitive costs and complex real-world constraints. Although emerging video generation…
Beyond Memorization: A Multi-Modal Ordinal Regression Benchmark to Expose Popularity Bias in Vision-Language Models
We expose a significant popularity bias in state-of-the-art vision-language models (VLMs), which achieve up to 34% higher accuracy on famous buildings compared to ordinary ones, indicating a reliance on memorization over generalizable…
Next-Embedding Prediction Makes Strong Vision Learners
Inspired by the success of generative pretraining in natural language, we ask whether the same principles can yield strong self-supervised visual learners. Instead of training models to output features for downstream use, we train them to…
Are We Ready for RL in Text-to-3D Generation? A Progressive Investigation
Reinforcement learning (RL), earlier proven to be effective in large language and multi-modal models, has been successfully extended to enhance 2D image generation recently. However, applying RL to 3D generation remains largely unexplored…
Urania: Differentially Private Insights into AI Use
We introduce $Urania$, a novel framework for generating insights about LLM chatbot interactions with rigorous differential privacy (DP) guarantees. The framework employs a private clustering mechanism...
Reinventing Clinical Dialogue: Agentic Paradigms for LLM Enabled Healthcare Communication
Clinical dialogue represents a complex duality requiring both the empathetic fluency of natural conversation and the rigorous precision of evidence-based medicine. While Large Language Models possess unprecedented linguistic capabilities,…
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…