Event owner lens
Use this record to benchmark whether a comparable event makes the work after the room visible. The score is 40/100, so the next move is to benchmark the weakest pillars before repeating the format.
technology ai startup agenda agenda analysis
ICML - WCA4Z Platform - Accelerating Legacy Code Modernization Using AI Agents, Deep Program Analysis, and - Workshops - The 1st Workshop on Vector...
This technology ai startup agenda in Technology / AI / Startup shows 26 visible agenda rows from icml.cc and scores 40/100: a moderate design signal with incomplete evidence. The clearest public signals sit in Future-of-Work Fit and Participation Architecture; the main limits are Follow Through and Network Design. Visible mechanisms include Participant work, Network design, and Learning transfer. The public record does not show follow-up or tracking, so the score should be read as design intent rather than... A practical reading: For a reader, this is a comparison record more than a model to copy: it reads as a technology ai startup agenda, with the strongest visible signal in future-of-work fit and participation architecture and the biggest open question around follow through and network design. The practical test is whether the published agenda connects the room to post-event continuation and evidence. This page is an original public-evidence analysis, not a copy of the source agenda or an endorsement of the event. The score places the visible agenda in the moderate design signal band. The strongest visible pillars are Future-of-Work Fit, Participation Architecture, and Learning Transfer; the thinnest visible pillars are Follow Through, Network Design, and Personalization. Visible mechanisms include Participant work, Network design, and Learning transfer. The extracted agenda preview includes 47 visible rows. The most common formats are Unknown, Keynote, and Workshop; the most common inferred purposes are Unknown, Showcase, and Knowledge Transfer.
Eight-pillar fingerprint
Hover any pillar to see what it measures and, where it scored low, what the agenda is missing.
Participation Architecture?58
Participation Architecture - 58/100. Participant work, contribution, interaction, and alternatives to passive broadcast.
Follow Through?5
Follow Through - 5/100. Owners, dates, commitments, progress checks, and accountability after the room.Missing: Add named owners, dates, implementation checkpoints, and a visible post-event continuation path.
Problem Specificity?40
Problem Specificity - 40/100. A clear costly problem, objective, decision, or performance target.
Personalization?34
Personalization - 34/100. Role, path, goal, preparation, or connection tailoring for participants.Missing: Create role-based paths, prepared questions, tailored breakouts, or participant-specific next steps.
Network Design?16
Network Design - 16/100. Structured weak ties, bridge-building, mixers, and relationship persistence.Missing: Replace generic networking blocks with designed introductions, ask-offer exchanges, peer groups, or bridge-building rituals.
Learning Transfer?58
Learning Transfer - 58/100. Applied practice, feedback, workplace use, refreshers, and 30-90 day transfer.
Evidence Maturity?45
Evidence Maturity - 45/100. Baseline, comparison, follow-up, isolation, and attribution confidence.
Future-of-Work Fit?65
Future-of-Work Fit - 65/100. Value against time, hybrid reality, accessibility, AI, and meeting load.
Fix the gaps
Field-tested exercises matched to this agenda's weakest pillars, from the exercise library.
Follow Through (5/100)
Exercises that strengthen it: Mental Toughness Workshop • WorkshopBank · 15% Solutions • WorkshopBank · Network Patches
Network Design (16/100)
Exercises that strengthen it: Fun Trust-Building Group Game for Team Connection - Izzat... · Exciting Group Trust Activity for Building Confidence... · PFP: September 2005
Personalization (34/100)
Exercises that strengthen it: Journey Mapping • WorkshopBank · Group Energiser & Perspective-Changing Exercise - Paradigm... · Photo Storytelling
Agenda Preview
The actual agenda we captured. Every block is classified by format and purpose. Open any block to see how we read it; the colored edge shows whether it is participant work, broadcast, logistics, or a showcase.
Room vs wrapper
23 percent of the 47 classified blocks put participants to work; the rest broadcast, show, or handle logistics. That mix is what drives the participation score.
Participant workBroadcastShowcaseLogistics
all eventTutorialsTrainingSkill building+
Format · Participant workTrainingGuided skill building where participants practice. Counts as participant work and learning transfer.
Evidence basisParticipant work is implied by the formatInferred from format
all eventSpotlight PostersPoster sessionShowcase+
Format · ShowcasePoster sessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisOutcome inferred from formatInferred from format
all eventWorkshopsWorkshopParticipant work+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisParticipant work is implied by the formatInferred from format
all eventWorkshopWorkshopParticipant work+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisParticipant work is implied by the formatInferred from format
all eventThe 1st Workshop on Vector DatabasesWorkshopParticipant work+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisParticipant work is implied by the formatInferred from format
8:30 AMOpening Remarks Yusuke Matsui VideoOpeningOrientation+
Format · BroadcastOpeningFormat not classified from the source; treated as a broadcast block by default.
Evidence basisNo participant output visible from this rowRead from source, no work signal
8:40 AMKeynote 1: Vector search for machine learning and machine learning for vector search Matthijs Douze VideoKeynoteExpert framing+
Format · BroadcastKeynoteA featured talk from the stage. Builds awareness and energy, produces no participant output on its own.
Evidence basisNo participant output visible from this rowRead from source, no work signal
9:30 AMOral 1: A Bi-metric Framework for Efficient Nearest Neighbor Search Haike Xu ⋅ Piotr Indyk ⋅ Sandeep Silwal VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
9:50 AMOral 1: The RaBitQ Library Jianyang Gao ⋅ Yutong Gou ⋅ Yuexuan Xu ⋅ Jifan Shi ⋅ Zhonghao Yang ⋅ Cheng Long VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
10:10 AMOral 1: IVF$^{2}$ Index: Fusing Classic and Spatial Inverted Indices for Fast Filtered ANNS Ben Landrum ⋅ Magdalen Manohar ⋅ Mazin Karjikar ⋅ Laxman Dhulipala VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
10:30 AMPoster Session 1Poster sessionShowcase+
Format · ShowcasePoster sessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisOutcome inferred from formatInferred from format
all event→ Don’t Lag, RAG: Training-Free Adversarial Detection Using RAG Roie Kazoom ⋅ Raz Lapid ⋅ Moshe Sipper ⋅ Ofer Hadar LinkTrainingSkill building+
Format · Participant workTrainingGuided skill building where participants practice. Counts as participant work and learning transfer.
Evidence basisParticipant work is implied by the formatInferred from format
12:00 PM1:00 PM Keynote 2: GPU-oriented High-Performance Graph-based Approximate Nearest Neighbor Search Hiroyuki Ootomo VideoKeynoteExpert framing+
Format · BroadcastKeynoteA featured talk from the stage. Builds awareness and energy, produces no participant output on its own.
Evidence basisNo participant output visible from this rowRead from source, no work signal
1:00 PMKeynote 2: GPU-oriented High-Performance Graph-based Approximate Nearest Neighbor Search Hiroyuki Ootomo VideoKeynoteExpert framing+
Format · BroadcastKeynoteA featured talk from the stage. Builds awareness and energy, produces no participant output on its own.
Evidence basisNo participant output visible from this rowRead from source, no work signal
1:45 PMPoster Session 2Poster sessionShowcase+
Format · ShowcasePoster sessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisOutcome inferred from formatInferred from format
3:00 PMCoffee BreakBreakPacing+
Format · LogisticsBreakA pacing or recovery block between sessions.
Evidence basisOutcome inferred from formatInferred from format
3:30 PMKeynote 3: Vector Search for Large-Scale Genomic Discovery Prashant Pandey VideoKeynoteExpert framing+
Format · BroadcastKeynoteA featured talk from the stage. Builds awareness and energy, produces no participant output on its own.
Evidence basisNo participant output visible from this rowRead from source, no work signal
4:15 PMOral 2: $alpha$-Reachable Graphs for Multi-vector Nearest Neighbor Search Siddharth Gollapudi ⋅ Ravishankar Krishnaswamy ⋅ Ben Landrum ⋅ Nikhil Rao ⋅ Kirankumar Shiragur ⋅ Sandeep Silwal ⋅ Harsh Wardhan VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
4:35 PMOral 2: Enhancing Retrieval Systems with Inference-Time Logical Reasoning Felix Faltings ⋅ Wei Wei ⋅ Yujia Bao VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
4:55 PMOral 2: Down with the Hierarchy: The ‘H’ in HNSW Stands for “Hubs” Blaise Munyampirwa ⋅ Vihan Lakshman ⋅ Benjamin Coleman VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
5:15 PMClosing Remarks Yusuke Matsui VideoClosingOrientation+
Format · BroadcastClosingFormat not classified from the source; treated as a broadcast block by default.
Evidence basisNo participant output visible from this rowRead from source, no work signal
all eventTutorialsTrainingSkill Building+
Format · Participant workTrainingGuided skill building where participants practice. Counts as participant work and learning transfer.
Evidence basisMediumRead from source
all eventMain ConferenceUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisLowRead from source
all eventSpotlight PostersPoster SessionShowcase+
Format · ShowcasePoster SessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisMediumRead from source
all eventWorkshopsWorkshopCo Creation+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisMediumRead from source
all eventCommunityUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisLowRead from source
all eventRocketChat Desktop ClientUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisLowRead from source
all eventWorkshopWorkshopCo Creation+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisMediumRead from source
all eventThe 1st Workshop on Vector DatabasesWorkshopCo Creation+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisMediumRead from source
all eventVector databases (Vector DBs) are a foundational and critical application layer for injecting information into large language models (LLMs). Although different companies have proposed various vector databases, no academic workshop has previously existed to discuss these systems comprehensively. This workshop aims to foster discussions on vector databases from various perspectives, ranging from mathematical theories to implementation-level optimizations. Topics covered in the workshop include retrieval-augmented generation (RAG), algorithms and data structures for approximate nearest neighbor search (ANN), data management systems for handling vector data, query languages, and embedding models. Furthermore, the workshop will also function as a platform for companies and researchers working on vector databases to present technical details (white papers) and exchange ideas.WorkshopCo Creation+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisMediumRead from source
all eventTimezone: America/LosAngelesUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisLowRead from source
8:30 AMOpening Remarks Yusuke Matsui VideoOpening RemarksOrientation+
Format · BroadcastOpening RemarksFraming or welcome from the stage. Orients the room, not participatory.
Evidence basisMediumRead from source
8:40 AMKeynote 1: Vector search for machine learning and machine learning for vector search Matthijs Douze VideoKeynoteThought Leadership+
Format · BroadcastKeynoteA featured talk from the stage. Builds awareness and energy, produces no participant output on its own.
Evidence basisMediumRead from source
9:30 AMOral 1: A Bi-metric Framework for Efficient Nearest Neighbor Search Haike Xu ⋅ Piotr Indyk ⋅ Sandeep Silwal VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
9:50 AMOral 1: The RaBitQ Library Jianyang Gao ⋅ Yutong Gou ⋅ Yuexuan Xu ⋅ Jifan Shi ⋅ Zhonghao Yang ⋅ Cheng Long VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
10:10 AMOral 1: IVF$^{2}$ Index: Fusing Classic and Spatial Inverted Indices for Fast Filtered ANNS Ben Landrum ⋅ Magdalen Manohar ⋅ Mazin Karjikar ⋅ Laxman Dhulipala VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
10:30 AMPoster Session 1Poster SessionShowcase+
Format · ShowcasePoster SessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisMediumRead from source
all event→ Don’t Lag, RAG: Training-Free Adversarial Detection Using RAG Roie Kazoom ⋅ Raz Lapid ⋅ Moshe Sipper ⋅ Ofer Hadar LinkTrainingSkill Building+
Format · Participant workTrainingGuided skill building where participants practice. Counts as participant work and learning transfer.
Evidence basisMediumRead from source
12:00 PM1:00 PM Keynote 2: GPU-oriented High-Performance Graph-based Approximate Nearest Neighbor Search Hiroyuki Ootomo VideoKeynoteThought Leadership+
Format · BroadcastKeynoteA featured talk from the stage. Builds awareness and energy, produces no participant output on its own.
Evidence basisMediumRead from source
1:00 PMKeynote 2: GPU-oriented High-Performance Graph-based Approximate Nearest Neighbor Search Hiroyuki Ootomo VideoKeynoteThought Leadership+
Format · BroadcastKeynoteA featured talk from the stage. Builds awareness and energy, produces no participant output on its own.
Evidence basisMediumRead from source
1:45 PMPoster Session 2Poster SessionShowcase+
Format · ShowcasePoster SessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisMediumRead from source
3:00 PMCoffee BreakBreakWellbeing+
Format · LogisticsBreakA pacing or recovery block between sessions.
Evidence basisMediumRead from source
3:30 PMKeynote 3: Vector Search for Large-Scale Genomic Discovery Prashant Pandey VideoKeynoteThought Leadership+
Format · BroadcastKeynoteA featured talk from the stage. Builds awareness and energy, produces no participant output on its own.
Evidence basisMediumRead from source
4:15 PMOral 2: $\alpha$-Reachable Graphs for Multi-vector Nearest Neighbor Search Siddharth Gollapudi ⋅ Ravishankar Krishnaswamy ⋅ Ben Landrum ⋅ Nikhil Rao ⋅ Kirankumar Shiragur ⋅ Sandeep Silwal ⋅ Harsh Wardhan VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
4:35 PMOral 2: Enhancing Retrieval Systems with Inference-Time Logical Reasoning Felix Faltings ⋅ Wei Wei ⋅ Yujia Bao VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
4:55 PMOral 2: Down with the Hierarchy: The ‘H’ in HNSW Stands for “Hubs” Blaise Munyampirwa ⋅ Vihan Lakshman ⋅ Benjamin Coleman VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
5:15 PMClosing Remarks Yusuke Matsui VideoClosing RemarksOrientation+
Format · BroadcastClosing RemarksClosing framing from the stage. Wraps the event, not participatory.
Evidence basisMediumRead from source
The Full Reading
Why It Ranks This Way +
Calibrated from GES design 40/100 and verified 40/100 with no fourth-loop cap.
Reader Takeaway. For a reader, this is a comparison record more than a model to copy: it reads as a technology ai startup agenda, with the strongest visible signal in future-of-work fit and participation architecture and the biggest open question around follow through and network design. The practical test is whether the published agenda connects the room to post-event continuation and evidence.
Strongest signals: Future-of-Work Fit, Participation Architecture, and Learning Transfer. Weakest signals: Follow Through, Network Design, and Personalization.
How This Agenda Could Improve +
- Add named owners, dates, implementation checkpoints, and a visible post-event continuation path.
- Replace generic networking blocks with designed introductions, ask-offer exchanges, peer groups, or bridge-building rituals.
- Create role-based paths, prepared questions, tailored breakouts, or participant-specific next steps.
Fastest next move: Add named owners, dated next steps, and a visible continuation path before treating the event as outcome-ready.
Role-Specific Reading +
Sponsor lens
Look beyond exposure. Strong sponsor value would show qualified interaction, problem work, buyer learning, customer evidence, or follow-up. The practical sponsor move is to look for structured introductions, buyer-seller fit, and relationship persistence.
Designer lens
The agenda is useful as a pattern sample from icml.cc. Redesign attention should go first to the lowest-scoring pillars; in practice, turn the thinnest agenda blocks into participant work.
Executive lens
Treat the visible agenda as an operating plan. The executive move is to require owners, dates, and evidence before treating the event as strategic. If owners, proof, and follow-through are not visible, the public record does not yet prove strategic movement.
Aggregator lens
Treat the source URL as evidence, not decoration. The data-product move is to label the source boundary clearly before ranking the record before ranking or syndicating the record.
What GES Means Here +
The Gathering Effectiveness Score is a strict 0-100 public-evidence reading of the agenda across eight pillars. It rewards visible participant work, follow-through, transfer, network design, and proof mechanisms more than polish, speaker fame, attendance, or satisfaction.
Visible mechanisms: Participant work, Network design, Learning transfer.
Evidence boundary: Scores reflect visible agenda/source evidence and should not be read as proof of causal event impact.
Limitations, Score Caps, and Review Flags +
Limitations
- No visible follow-up, progress monitoring, or longitudinal tracking.
- No baseline measurement is visible.
Score caps
- No fourth-loop score cap applied.
Review flags
- No source-backed follow-up, validation, baseline, tracking, or impact evidence.
- No tracking, validation, feedback, or impact measurement found in the visible source text.
Is this proof the event worked? +
No. This is a strict public-evidence reading of the agenda. Proof would require baseline, comparison, follow-up, attribution, and impact evidence beyond the listing.
What should a reader inspect first? +
Start with the source URL, then compare the eight pillar scores against the agenda rows. The biggest opportunities usually sit in follow-through, evidence maturity, and participant work.
Why publish weak records? +
Weak records are part of the map. They show where public agendas still describe sessions and speakers more often than outcomes, commitments, transfer, or proof.
How should I use the rows? +
Read the agenda rows as the visible design trace: formats, purposes, and evidence labels show what the public source made inspectable, not everything that happened in the room. This is a source-grounded interpretation of the public agenda record, not a copy of the source, and not an endorsement of the event.
Embed the verified badge +
This record is in the hand-verified gold set. Copy the snippet below to embed the verified badge on your own site.
<a href="https://unitedwetransform.com/events/evt_2025_icml_wca4z_platform_accelerating_legacy_code_modernization_using_ai_agents_f10492"><img src="https://unitedwetransform.com/badge/ges-verified.svg" alt="GES verified by United We Transform" height="40"></a>Where To Go Next
Compare this agenda against other Technology / AI / Startup events scored on the same eight pillars.