Researcher bridging open full-duplex speech-to-speech systems and value-sensitive studies of everyday AI agent use
2
papers here
2
reviewed by Evolve
0
first-author
0
corresponding
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works · OpenAlex
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h-index · OpenAlex
Bibliometric figures come from OpenAlex (2026-10-15) and cover the author's entire public record, not just the papers listed here. Reproducibility signal comes from Evolve's own reviews.
Research profile
Output—
Not yet scored: no publication-volume or venue-count data is available in the current snapshot. This axis would measure total papers, venue mix, and productivity over time; only the two cataloged 2026 arXiv papers exist as evidence so far.
Impact—
Not yet scored: citation counts, h-index, and influence metrics are absent from the input data. This axis would measure how widely the cataloged work is cited across fields; no estimate should be inferred from the available evidence.
Focus0/100
The focus score is 0 because the raw field distribution is an exact 50/50 split: 0.5 speech processing and conversational AI, 0.5 human-computer interaction / AI agent studies. The two cataloged papers embody each side — a full-duplex speech-to-speech system on one track, a Value Sensitive Design analysis of agent delegation on the other. This is a balanced two-track portfolio rather than scattered work, but the metric registers it as low concentration.
Collaboration83/100
Collaboration is the strongest measured axis at 83, grounded in 64 distinct coauthors across the bibliometric record and a recurring core of 12 frequent collaborators — including Jagadeesh Balam, Edresson Casanova, Zhehuai Chen, and Harishchandra Dubey — concentrated on the speech-systems track. On both cataloged papers Chen Chen appears as a middle author without corresponding status, a profile consistent with contributing inside large team efforts like the VoiceChat release.
Activity—
Not yet scored: the data contains no year-by-year publication cadence, so recent output velocity cannot be computed. This axis would measure publishing frequency and recency of work; the input only anchors both cataloged papers to 2026.
Reproducibility55/100
The reproducibility score of 55 is a mean over exactly 2 papers with reproducibility evidence (reproMean 55, reproPapers 2), and both cataloged papers carry a medium readiness rating. The VoiceChat paper ships an open model whose reported argument accuracy (42.2%, Pass@1 33.0%) is checkable; the OpenClaw study's LLM-assisted pipeline over 73k Reddit posts is replicable, though Evolve flags circularity risk in its fulfillment-outcome link.
Research summary
Chen Chen, affiliated with Florida International University in this name-resolved profile, presents a two-sided 2026 research portfolio at the intersection of conversational AI engineering and human-centered AI analysis. The Evolve catalog holds two arXiv papers, both with Chen Chen as a middle, non-corresponding author. The first, NemotronLabs VoiceChat, is the first open full-duplex speech-to-speech model with native tool calling; Evolve credits strong turn-taking and barge-in handling but reports weak argument accuracy (42.2%, Pass@1 33.0%). The second applies Value Sensitive Design to 73,000 Reddit posts about OpenClaw, finding that values attach to the conditions of delegation rather than to the outputs produced. The bibliometric field distribution reflects this split exactly — 0.5 speech processing and conversational AI, 0.5 HCI/AI agent studies — which drives the focus score to 0. Collaboration is the strongest measured dimension at 83, backed by 64 distinct coauthors and a recurring 12-name core team spanning both tracks. Reproducibility scores 55 as a mean over two papers, each rated medium readiness. Output, impact, and activity metrics are missing from the current snapshot, so this profile should be read as early-stage: substantive recent work, but without verified citation or volume evidence.
Collaboration pattern
The measured collaboration signal is strong: score 83 with 64 distinct coauthors. Twelve recurring collaborators include Jagadeesh Balam, Travis Bartley, Edresson Casanova, Zhehuai Chen, Harishchandra Dubey, and Slim Essid — a roster consistent with the large-author-group speech-systems track. On both cataloged papers Chen Chen is a middle, non-corresponding author, indicating a contributor position within group projects rather than solo or senior-led work.
Research keywords
Highlights
Value-sensitive delegation: 73k Reddit posts show values attach to how agents are used, not what they output
First open full-duplex speech-to-speech model with native tool calling
Timeline
- 2026Co-authored (middle position) the NemotronLabs VoiceChat paper — the first open full-duplex speech-to-speech model with native tool calling.
- 2026Published the Value-Sensitive Delegation study, a Value Sensitive Design analysis of 73,000 Reddit posts on everyday AI agent use via OpenClaw.
- 2026Both cataloged papers land in the same year, splitting the portfolio evenly between speech/conversational AI engineering and HCI/AI-agent value analysis (field distribution 0.5/0.5).
Papers in the Evolve catalog
Frequent co-authors
About this profile
This profile is AI-structured by Evolve.Pub from public bibliographic data (OpenAlex) and Evolve's own paper reviews. It is not written or endorsed by the researcher unless the profile is claimed. Radar dimensions are computed from real bibliometrics with fixed formulas — raw figures are shown alongside; missing dimensions mean insufficient data, never zero. Errors? Claim the profile to correct or hide it.
- Bibliometric dimensions are computed from OpenAlex-sourced data only; the output, impact, and activity axes lack underlying metrics (no citation counts, h-index, or publication volumes).
- 'Chen Chen' is a common name: this profile is name-resolved from public bibliographic data, and both cataloged papers are arXiv preprints whose peer-reviewed status is unverified.
- The reproducibility score (55) is averaged over only 2 papers, both rated medium; the sample is too small to generalize.
- No country or ORCID was provided, and the Florida International University affiliation is not independently verified in the input data.