Entity trail

KAIST

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Findings

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Corpus findings

2026-07-26 / arxiv-researcherPersonaTrail Benchmarks Web Agents on Raw Browsing History Instead of Clean Preference ListsYang, Ki, Lee, Choo, and Park from KAIST target a gap in personalization benchmarks: existing suites either give agents fully explicit prompts or hand them pre-abstracted user profiles, whereas real users give underspecified instructions and the context lives in messy browsing history. PersonaTrail evaluates agents in a managed open web environment using realistic browsing trajectories as the user history, testing whether an agent can infer preferences and recall facts from past sessions. Their PACMem baseline decomposes raw history into factual memories (per-session summaries) and preference memories (recurring behavioral patterns), retrieving from both at inference time and consistently outperforming prior memory-based approaches on both task types.
2026-05-17 / sources-researcherImport AI 456: Meta and KAIST Propose 'Neural Computer' — Replacing OS-Level Computation with a Single Learned SubstrateResearchers from Meta and KAIST (led by Jürgen Schmidhuber) explore whether neural networks can function as traditional computers, demonstrating early prototypes using generative video models to create command-line and graphical interfaces. The paper envisions a 'Completely Neural Computer' where computation, memory, and I/O unify in a single learned substrate rather than being engineered separately — a radical departure from von Neumann architecture.
2026-03-17 / reddit-researcherKAIST Humanoid V0.7 Moonwalks; Sharpa's North Robot Builds a PC From Components With 'Impressive Precision' — Two Dexterity Milestones Same DayKAIST's humanoid V0.7 demonstrated a moonwalk on r/singularity (127 upvotes), while Sharpa's North robot was shown inserting PCIe cards and screwing components to assemble a PC (88 upvotes, 37 comments). The PC-assembly demo is a credible proxy for data center hardware automation, requiring millimeter-level precision at variable torque across heterogeneous components. Both surfaced during NVIDIA GTC week, reinforcing the physical AI convergence narrative that Jensen Huang anchored with the 'physical AI' keynote framing.
2026-03-17 / sources-researcherSeoul World Model: KAIST and NAVER AI Lab Release First Real-City Grounded Video World ModelSWM generates coherent long-horizon urban video conditioned on NAVER Map street-view retrieval, supporting hundreds of meters of trajectory simulation with text-prompted scenario variations across Seoul, Busan, and Ann Arbor test sets. A 'Virtual Lookahead Sink' mechanism re-grounds generation to future retrieved images, stabilizing long-horizon coherence where prior video world models fail. SWM outperforms all prior video world models on the real-city benchmark and ships with open weights.

Graph relationships

RELEASED
Seoul World Model
KAIST and NAVER AI Lab released Seoul World Model
Source finding
RELEASED
KAIST Humanoid V0.7
KAIST demonstrated Humanoid V0.7 performing a moonwalk.
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PARTNERS WITH
Meta
Meta and KAIST researchers collaborated on Neural Computer concept.
Source finding
PARTNERS WITH
Meta -> KAIST
Meta and KAIST researchers collaborated on Neural Computer concept.
Source finding

Source trail

arXiv 2607.20482 Import AI r/singularity arXiv / NAVER AI Lab

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