Agents4Science Conference is a modern meeting exploring autonomous, LLM-driven AI agents for collaborative scientific discovery.
It features a sustainable decentralized model with regional hubs, rolling peer review, and carbon-neutral practices to address logistical and ecological challenges.
Robust data analytics and strategyproof peer-review mechanisms support equitable author matching and continuous impact assessment.
The Agents4Science Conference is a prototypical contemporary scientific meeting operating at the intersection of artificial intelligence, computational science, and agent-based research paradigms. It serves as a focal point for presenting advances in LLM-driven research automation, novel community-building models, carbon-aware event planning, and the deployment of conference-assisting technologies. The structure, metrics, and operational principles of Agents4Science reflect and synthesize current methodological research on scientific meetings, data-driven event analytics, sustainability policy, and robust peer review.
1. Agentic Paradigm and Scientific Conference Innovation
Agents4Science was established to address core inefficiencies of traditional scientific discovery by foregrounding the role of LLM-driven agents across all levels of research, from granular tool use to networked scientific collectives. The event draws heavily on the Agent4S “Fifth Paradigm” framework, advancing the notion that scientific progress is increasingly mediated by autonomous, collaborative, and self-improving AI systems. The conference explores:
The progression from single-tool automation to fully autonomous “AI scientists” orchestrating closed-loop experimental cycles.
Technical interoperation of Model-Context-Protocol (MCP), agent-to-agent (A2A) communication, and full-process laboratory autonomy.
Scalable agentic infrastructures for distributed, multi-lab scientific discovery, emphasizing LLM-enabled planning, coordination, and cross-disciplinary synthesis (2506.23692).
Agents4Science’s programming, invited sessions, and challenge tracks center on real-world deployment of agentic research stacks, workflow orchestration, reproducibility protocols, and implications for the organization and longevity of scientific networks.
2. Sustainable and Decentralized Conference Models
The conference implements policies targeting the environmental, logistical, and inclusivity crises identified in contemporary scientific event models. Key design adaptations, grounded in analyses of AI conference unsustainability (Chen et al., 6 Aug 2025) and quantitative carbon accounting (Streb et al., 2022), include:
Regional federation: Replacing a single central event with networked regional hubs, minimizing aggregate flight miles and logistical bottlenecks.
Rolling peer-review: Decoupling submission, review, and presentation timelines with global, online-managed review processes, addressing both review capacity and the “research lifecycle lag”.
Carbon-neutral operations: Systematic measurement of total and per capita carbon emissions, transparent reporting, opt-out offset fees (calculated as
$\text{Offset Fee} = (\text{CO}_2 \text{ per delegate}) \times (\$\text{ per t CO}_2)),andcommitmenttofulllocalemissionsremovalwithpartialorcompletetraveloffsetting.</li><li>Community−centricmentalhealthandwell−beingstrategies:Smallerhubsizes,asynchronousdigitalpostersessions,andembeddednetworkstocombatisolationandburnout.</li><li>Feedbackloops:Institutionalizationofpre−andpost−eventsurveystargetingsustainability,equity,andexperiencemetricstodriveiterativeimprovement.</li></ul><p>ThismultifacetedapproachoperationalizesaCommunity−FederatedConference(CFC)architecture,aimingtoremediatethescaling,ecological,andpsychologicalpressuresthatunderminelegacymega−events.</p><h2class=′paper−heading′id=′data−analysis−impact−measurement−and−archival−practices′>3.DataAnalysis,ImpactMeasurement,andArchivalPractices</h2><p>Agents4Scienceleveragescloud−basedrepositories(e.g.,OpenResearch(<ahref="/papers/1711.04548"title=""rel="nofollow"data−turbo="false"class="assistant−link"x−datax−tooltip.raw="">Behrendetal.,2017</a>))forcomprehensiveeventdatacuration,analysis,anddissemination.Corepracticesinclude:</p><ul><li>Semanticdatacaptureandarchival:Automatedextractionandpreservationofeventwebsites,proceedings,participantlists,feestructures,acceptancerates,andcommitteecomposition.</li><li>SPARQL−enabledanalytics:Exposureofallmetadatafortrendanalysis(e.g.,acceptancerates,serieslongevity,registrationfeeescalation,programcommitteediversity),cross−eventbenchmarking,andcitationlinkage.</li><li>Integrationwithbibliometricimpactmeasurement:ProceedingsindexedinScopusandSJR,withquartileassignmentviacomputedthresholding</li></ul><p>Q(s) =
\begin{cases}
Q1, & s \geq T_1 \
Q2, & T_2 \leq s < T_1 \
Q3, & T_3 \leq s < T_2 \
Q4, & s < T_3
\end{cases}</p><p>toenableobjectiverankingandequivalenceassessmentagainstbothjournalandconferenceoutputs(<ahref="/papers/2010.01540"title=""rel="nofollow"data−turbo="false"class="assistant−link"x−datax−tooltip.raw="">Kochetkovetal.,2020</a>).</p><ul><li>Continuousmeta−analysisfororganizationalstrategy,trenddetection,andpolicybenchmarking.</li></ul><p>ThisstructureddatainfrastructureensuresthatAgents4Sciencemeetsbotharchivalandanalyticalstandardsforlongitudinalstudiesofconferencequality,inclusiveness,andresearchimpact.</p><h2class=′paper−heading′id=′participatory−dynamics−and−community−structure′>4.ParticipatoryDynamicsandCommunityStructure</h2><p>QuantitativeanalysesandtheoreticalmodelingofparticipantbehaviorsatscientificconferencesareintegraltoAgents4Science’sdesign(<ahref="/papers/1510.08622"title=""rel="nofollow"data−turbo="false"class="assistant−link"x−datax−tooltip.raw="">Smiljanicˊetal.,2015</a>,<ahref="/papers/2212.04242"title=""rel="nofollow"data−turbo="false"class="assistant−link"x−datax−tooltip.raw="">Mryglod,2022</a>).Theevent’sstructureexplicitlytargets:</p><ul><li>Associativeparticipationreinforcement:Earlyinclusionandrepeatattendancearepromotedtomaximizethepositivefeedbackeffect,increasingtheprobabilityofongoingengagementasdescribedby:</li></ul><p>g(x, y) = \frac{x^p}{x^p+(y+y_0)^p}</p><p>wherexispriorparticipations,ymissedevents,pfeedbackstrength,andy_0$ community inclusiveness index.
Balance of stable core and newcomer influx: Statistical patterns (truncated power laws in participations, co-authorship) and community-building practices aim for a robust mix of established and first-time participants. Analysis reveals sustained vibrancy when roughly half of annual participants are newcomers; 27% of newcomers typically return, evidencing successful integration (Mryglod, 2022).
Ego-centric mapping: Visual and metric-based profiling of participant-conference reciprocal impact (e.g., node degree, centrality, introduction of new collaborators, and geographical expansion).
A plausible implication is that nurturing inclusiveness, social ties, and mentoring, especially in early years of participation, strongly increases the scientific and network value of Agents4Science for both individuals and the community.
5. Peer Review Design and Strategyproof Mechanisms
Agents4Science implements theoretically grounded, manipulation-resistant peer review protocols, reflecting state-of-the-art in social choice theory for reviewer-authorship overlap (Xu et al., 2018). The process features:
Partitioned assignment: The conflict (authorship) graph is algorithmically partitioned into two (or more) disconnected components; reviewers in each group evaluate submissions from the complementary group, preventing any reviewer from reviewing their own (conflict) papers.
Aggregation and group unanimity: Final rankings are derived by within-group aggregation (e.g., Borda count), followed by deterministic interleaving, ensuring the property that no reviewer can affect the ranking of their own papers, and group consensus is faithfully reflected.
Empirical validation: Analysis on real conference data demonstrates modest decreases (~11%) in mean expertise-match assignment scores compared to unconstrained matching, a practically tolerable trade-off for strategyproofness guarantees.
Recognition of impossibility frontiers: Higher-order consensus properties (pairwise unanimity) or connected assignment graphs are provably incompatible with nontrivial strategyproofness.
This design materially reduces incentives for strategic manipulation, while preserving group decision quality and the operational scalability necessary for modern multi-track events.
6. Author–Conference Matching and Recommendation Systems
Agents4Science uses correspondence analysis–based (CA) frameworks for venue recommendation and session personalization (Iyer et al., 2020, Kostric et al., 2022):
Author-conference matching: CA is applied to Author × Conference, Paper × Word, and Word × Conference matrices for dimensionality reduction and principal coordinate analysis, supporting robust recommendations even for first-time or network-isolated authors.
Content- and network-based approaches: Conference recommendations are made by projecting paper metadata (tf-idf, LDA topics) and author profiles into low-dimensional spaces and finding nearest-neighbor matches in the conference domain.
Conversational assistants: In conjunction with digital infrastructure, DAGFiNN provides web- and robot-assisted, personalized navigation of program content and local information, integrating POI, session, and social recommendations, and supporting preference elicitation and engagement (Kostric et al., 2022).
These systems ensure equitable session exposure, more efficient research dissemination, and data-backed, individualized navigation through the event.
7. Conference Guidance, Networking, and Post-Event Integration
Agents4Science disseminates empirically validated best-practices for conference participation, as codified in structured rule sets (Leininger et al., 2021):
Lifecycle guidance: Preparation, funding, logistics, self-care, networking, engagement, and post-conference follow-up are addressed by a “Ten Simple Rules” framework, encompassing both in-person and virtual contexts.
Institutionalized mentorship and affinity groups: Dedicated resources and events for first-timers, underrepresented groups, and peer support are provided, structured by curated web portals and real-time digital platforms.
Emphasis on professional and social codes of conduct, safety, and efficient follow-up: Post-event workflows include systematic debriefing, CV/resume updates, and network maintenance.
The approach aligns with the overall paradigm of structured, data-driven, and inclusive scientific community-building, reinforcing the event’s role as both a research dissemination node and an accelerator for scholarly careers.
In summary, the Agents4Science Conference embodies the convergence of agent-driven research paradigms, sustainability directives, decentralized event management, quantitative network analysis, robust data infrastructure, and manipulation-resistant peer review. Its design and operation are systematically informed by recent advances in the science of science and conference organization literature, seeking to maximize research impact, community health, and paradigm-level scientific progress.