I Can't Join, But I Will Send My Agent: Stand-in Enhanced Asynchronous Meetings (SEAM)

Andrew Irlitti; Eduardo Velloso; Jarrod Knibbe; Jens Emil Gr{\o}nb{\ae}k; Zhongyi Bai

REVIEW 3 major objections 6 minor 67 references

I Can't Join, But I Will Send My Agent: Stand-in Enhanced Asynchronous Meetings (SEAM)

T0 review · 3 major / 6 minor · reviewed 2026-08-15 · deepseek-v4-flash

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Pith's one-line read Embodied stand-ins let absent colleagues stay in VR meetings—and catch up in first person.

desk verdict A worthwhile proof-of-concept for a novel asynchronous VR meeting format, but the headline 'enhancement' claim is not supported because there is no baseline condition. read the letter →

arxiv 2508.17676 v1 pith:X3AJQXFF submitted 2025-08-25 cs.HC

Zhongyi Bai , Jens Emil Gr{o}nb{ae}k , Andrew Irlitti , Jarrod Knibbe , Eduardo Velloso This is my paper · ORCID

classification cs.HC

keywords asynchronouscollaborationvirtualrealityembodiedconversationalagentstand-insocialpresencemeetingrecordingsWizard-of-Ozfirst-personperspective

verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper introduces SEAM—Stand-in Enhanced Asynchronous Meetings—in which a colleague who cannot attend a VR meeting sends an embodied virtual agent, configured with their responses to the agenda, to take their place. Attendees address the stand-in directly; later, the absent colleague watches the recording from the stand-in's first-person perspective and can pause it to record their own response. Through two Wizard-of-Oz studies with 45 participants, the authors aim to establish that this arrangement benefits both sides: present attendees gain access to preferences that push the decision forward, and absentees feel included by the social attention their stand-in attracted. The paper is a proof of concept for asynchronous meetings that feel more like synchronous conversations.

What carries the argument

The load-bearing mechanism is the stand-in itself: an embodied conversational agent that turns its gaze toward the active speaker, nods, and delivers pre-recorded responses to agenda items while shrugging, pointing, or gesturing to reinforce meaning. Because these behaviours are triggered in real time during the meeting, the stand-in is not a recording; it adapts to the conversation and gives attendees something to address. The second mechanism is the first-person playback: the absentee re-experiences the meeting from the stand-in's exact position and can pause playback to record a spoken, embodied reply, which is timestamped for inclusion in later iterations. Together they convert an absence into a deferred conversational presence.

What would settle it

Deploy the LLM-powered stand-in system the paper describes in a real multi-iteration meeting and count how often attendees address it after it makes an incorrect or delayed response; if addressing rates fall to near zero or absentees report that the stand-in's errors made them feel misrepresented, the claimed enhancement does not survive the move from Wizard-of-Oz to autonomous AI.

Watch

Extended reading notes

Core claim

The central discovery is that a stand-in can make an absent participant conversationally available without being synchronously present. In the studies, attendees addressed the stand-in as if it were the absentee, used its preconfigured answers as genuine input in deciding on a shared plan, and many reported perceiving three people in the room rather than two. Absentees who later watched the recording from the stand-in's viewpoint reported feeling included, because attendees had looked at, asked, and waited for their stand-in; the embodied attention, eye contact, and listening behaviours carried that feeling. The same data shows a measurable gap: the stand-in's social presence was rated lower than a live attendee's (about -0.75 standard units on the Networked Minds scale), and even a recording of real people retained some of that gap, so the paper's claim is that stand-ins enhance—not fully replicate—presence.

Load-bearing premise

The stand-in's behaviour was scripted and triggered by a researcher rather than produced by a real AI, so the user experiences reported here depend on the assumption that an autonomous stand-in would respond with comparable timing, accuracy, and naturalness.

Editorial extensions

If this is right

If the central claim holds, meeting software can let a missing stakeholder's preferences shape decisions during the live discussion instead of after the fact.
Absentees can catch up on meetings as an embodied participant rather than by reading notes or scrubbing a flat video, preserving the reasoning, affect, and attention that drove the decision.
Attendees will treat a well-behaved stand-in as a delayed participant, adapting their communication style as they discover what the stand-in can and cannot answer.
The measured social-presence gap implies that stand-ins will need better response intelligence and more human-like behaviour before they can stand in for someone in high-stakes meetings.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

Inference: the same design could extend to partial participation—a stand-in that escalates questions to the absentee over mobile messaging mid-meeting—moving SEAM from all-or-nothing absence to granular availability.
Inference: because participants said they wanted stand-ins to learn from past meetings and to sound like the absentee, the concept's long-term value may lie less in the avatar body and more in the memory and voice models that make responses feel attributable to a specific person.
Inference: the study's 'trigger words' finding suggests that if real AI stand-ins require explicit address (like 'Hey Lee') to respond, attendees may come to treat them as voice assistants; a testable design fix is to give stand-ins ambient, attention-based triggers instead.

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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Desk Editor's Note

read the letter

I read SEAM as an exploratory design study, not a comparative evaluation, so I was less bothered by the Wizard-of-Oz setup. The novel combination here is real: an embodied stand-in that attendees can converse with, plus later first-person replay from that stand-in's viewpoint for delayed participation. The closest prior work, Ditto, stayed in 2D and never put the absent user back in the scene; Wang et al. transformed recordings but did not have a live stand-in. The paper also gives a fairly complete description of an LLM-powered prototype, and the qualitative results are genuinely interesting—attendees alternated between treating the stand-in as human and as a limited bot, and absentees felt included largely because of eye contact and listening behaviors. The authors report their Bayesian ordinal models carefully, with compatibility intervals and an explicit warning against significance claims. They also acknowledge in Section 10 that the WoZ stand-in diverges from real AI constraints, and that participants were mostly students in the same room. So the paper is honest about its scope.

The soft spot is not the WoZ gap; it is that the central claim of 'enhancing' meetings is untested. Study 1 had no condition without a stand-in, and the task instructions explicitly told participants to take all three preferences into account. That makes the 14/15 groups outcome a compliance finding, not evidence that the stand-in drove inclusion. The quantitative comparisons show only that a stand-in yields lower social presence than a live human, not that it beats taking notes or watching a Zoom recording. So the abstract's 'can enhance meetings' goes beyond the data. This is a common exploratory-paper problem, and it is fixable: the authors could reframe the claim as 'a proof of concept with promising qualitative indicators' or add a modest comparison to an equivalent video-based condition.

I would send this to review. It deserves referee time because the design concept is timely and the implementation detail is useful, but I'd ask for the claims to be scaled back or the comparison added. If I were doing asynchronous-collaboration work, I'd cite it for the concept and the prototype description, not for the empirical 'enhancement' result.

Referee Report

3 major / 6 minor

Summary. The paper proposes SEAM (Stand-in Enhanced Asynchronous Meetings), a vision for asynchronous VR meetings in which an absent participant is represented by an embodied stand-in agent. Attendees interact with the stand-in during the meeting; later, the absentee watches the recording from the stand-in's first-person perspective and can add responses. The manuscript reports two mixed-method studies with 45 participants using a Wizard-of-Oz stand-in: Study 1 has pairs of attendees conducting a decision-making task with a stand-in and then watching the recording from the stand-in's viewpoint, while Study 2 has new participants watch the Study 1 recordings as true absentees. The qualitative analysis identifies themes about interaction strategies, social presence, decision-making, inclusion, and exclusion; the quantitative analysis uses Bayesian ordinal models to compare social presence ratings across conditions. The paper concludes that the stand-in 'can enhance meetings,' presents design implications and ethical/trust considerations, and describes a follow-on personalized LLM-powered stand-in system. The central stated contribution is a proof-of-concept user-experience exploration of embodied asynchronous meetings rather than a controlled comparative evaluation.

Significance. If the enhancement claim were supported, the paper would make a useful contribution to CSCW and HCI: it opens a design space for asynchronous embodied meetings, provides a working VR prototype, and offers concrete design considerations for stand-in representation, playback, and trust. The paper has genuine strengths: two complementary studies, a systematic inductive qualitative analysis, Bayesian ordinal models with compatibility intervals and explicit caveats, clear reporting of limitations, and a detailed system description. The largest weakness is that the headline comparative claim is not backed by a no-stand-in baseline condition, and the stand-in behavior was manually enacted by a researcher, so the results characterize a simulated stand-in rather than a real AI-powered one. With appropriate reframing or an additional baseline condition, the work could be a solid exploratory contribution; in its current form, the abstract and conclusion overstate the evidence.

major comments (3)

[Section 5, 5.2, 7.2.2, 11] The paper's headline claim that 'the stand-in can enhance meetings' (abstract; Section 11) is comparative, but the studies include no baseline condition in which an absentee is absent without a stand-in or in which attendees catch up via notes or recordings. Section 5 explicitly states no baseline was used, and Section 5.2 instructed participants that by the end of the meeting they 'should have agreed ... taking all three participants' preferences into account,' so the observation in Section 7.2.2 that 14/15 groups incorporated Lee's preferences is partly a compliance effect rather than evidence attributable to the stand-in. Table 1 only compares the stand-in and the recorded avatar against a live human attendee (-0.75 [-0.97, -0.61] SD for the stand-in on the perception-of-self subscale); it never shows whether the stand-in raises perceived social presence above a no-stand-in asynchronous practice. Consequently, the current data support an exploratory account of how attendees and absentees experience a WoZ stand-in, but they do not establish that SEAM enhances meetings relative to current asynchronous practice. I recommend either adding a baseline condition or reframing the contribution as an exploration of user experience with the enhancement claim explicitly qualified.
[Section 4.4, 9, 10] The stand-in in both user studies was Wizard-of-Oz controlled: Section 4.4 states the researcher manually played back recorded responses, and Section 10 concedes that the approach 'does not reflect the constraints, unpredictabilities, and response delays inherent in real-world AI systems.' Section 9 then presents a personalized LLM stand-in system, but that system was not evaluated with participants in the reported studies; its described behaviors (e.g., 'manage the discussion' and 'contribute input if topics of interest are mentioned') are claims about the prototype, not about measured user experience. The central user-experience findings therefore hold only for the manually enacted stand-in, and the paper should not imply that the LLM-powered version necessarily produces the same effects. Please either add an evaluation of the Section 9 system or clearly delimit all results to the technology probe.
[Section 7.1, Table 1, Table 5] The model specification for the social-presence analysis is inconsistent: the text gives 'Social presence ~ Attendance + (1|Participant) + (1|Questions)', Table 1's caption includes an additional '(1|Meetings)' term, and Table 5 reports the model without the Meeting random intercept. Because the reported compatibility intervals depend on which random effects are included, please align the formula in the text, tables, and appendix and confirm which random effects were used for the estimates in Table 1.

minor comments (6)

[Abstract] The sentence 'Present attendees can easily access information that drives decision-making in the meeting perceive high social presence of absentees' is missing a verb or punctuation; it should be rewritten for clarity.
[Section 2] Several subsection headings render as garbled placeholder characters (e.g., the heading following 'Non-verbal behaviours are crucial for face-to-face collaboration'), making related-work content difficult to read; the production/PDF encoding should be fixed.
[Section 5.2] The instruction 'taking all three participants' preferences into account' conflates the stand-in with Lee as a participant; since the paper later uses the 14/15 result as evidence, clarify how Lee was described to participants and whether they understood Lee as a person they should include.
[Section 7.1] The caption of Figure 12 says the intervals are 95% compatibility intervals, while the text says they are 'not 95% confidence intervals'; reword this to avoid confusing Bayesian compatibility intervals with frequentist confidence intervals.
[Section 8.1] The statement about the authors' own two months of use over eleven asynchronous meetings is anecdotal; it should not be offered alongside the user-study findings without an explicit label as informal first-hand experience.
[Section 10] The co-location caveat (participants performed the Study 1 task in the same room) should be stated where the quantitative social-presence results are first reported in Section 7.1, not only in Limitations.

Circularity Check

0 steps flagged · score 0.0 of 10

No circular reasoning found; the paper's claims are derived from empirical user-study data rather than from self-referential definitions or fitted inputs.

full rationale

This is an exploratory user-study paper rather than a formal derivation or predictive model, so the circularity patterns of self-definition, fitted-input-as-prediction, or imported uniqueness theorems do not apply. The central claim that SEAM 'can enhance meetings' is supported by participant questionnaires, qualitative interviews, and behavioral observations, with no equation or parameter fitted to the outcome being predicted. Author self-citations (e.g., [24], [30], [35], [36], [45], [46]) appear only in related-work discussions or as methodological precedents for Bayesian analysis, and none is load-bearing for the novelty claim or used to define away alternatives. The most salient weaknesses—the absence of a no-stand-in baseline and the task instruction that participants should take all three preferences into account—concern external validity and demand characteristics, not circularity, because the reported perceptions and decisions are not constructed from the same data used to define the intervention. The acknowledged Wizard-of-Oz limitation is a fidelity concern about the simulated AI, not a circular step. Accordingly, the appropriate finding is no significant circularity, with a score of 0.

Assumptions & free parameters 0 free parameters · 3 assumptions · 0 invented entities

The central claims rest on three domain assumptions: the Wizard-of-Oz stand-in approximates an AI-powered one, the simple planning task stands for real meetings, and the Networked Minds questionnaire captures VR social presence. The paper explicitly acknowledges the first two as limitations. No free parameters or invented entities are needed; this is an empirical user study of a software prototype.

assumptions (3)

domain assumption Wizard-of-Oz manual triggering of pre-recorded stand-in responses approximates the behavior of a future AI-powered stand-in.
The user-experience findings depend on this equivalence; Section 5 explains the choice and Section 10 concedes the approach does not reflect real AI constraints, unpredictability, or response delays.
domain assumption The weekend-planning task with a fictional absent friend is representative of the workplace meetings SEAM targets.
Section 10 states the simple topic may not generalize to formal or supervisory meetings and calls for testing with professionals.
domain assumption The Networked Minds questionnaire captures the socially important dimensions of presence in this VR setting.
Quantitative conclusions rely on this instrument, and the paper does not validate it for VR stand-in interaction specifically.

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Cite this review

Pith. "Pith review of I Can't Join, But I Will Send My Agent: Stand-in Enhanced Asynchronous Meetings (SEAM)." pith.science (2026). https://pith.science/paper/X3AJQXFF

@misc{pith2026250817676,
  author       = {Pith},
  title        = {Pith review of: I Can't Join, But I Will Send My Agent: Stand-in Enhanced Asynchronous Meetings (SEAM)},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/X3AJQXFF}},
  note         = {Machine review of arXiv:2508.17676}
}

read the original abstract

We propose and explore the user experience of SEAM -- Stand-in Enhanced Asynchronous Meetings -- virtual reality meetings in which embodied virtual agents represent absent users. During the meeting, attendees can address the agent, and the absent user can later watch the recording from its perspective to respond. Through two mixed-method studies with 45 participants using the Wizard-of-Oz approach, we explored both the perspectives of the attendees in the original meeting and of the absent users later re-watching the meeting. We found that the stand-in can enhance meetings, benefiting both present and absent collaborators. Present attendees can easily access information that drives decision-making in the meeting perceive high social presence of absentees. Absentees also felt included when watching recordings because of the social interactions and attention towards them. Our contributions demonstrate a proof of concept for future asynchronous meetings in which collaborators can interact conversationally more akin to how they would if it had been synchronous.

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