University of Pennsylvania NLP researcher working on cultural NLP and LLM benchmarks for network protocol reasoning
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—
No publication-volume data exists in this snapshot: no paper counts, venue list, or annual totals are recorded. This axis would measure how much the researcher publishes and in which venues, and it stays unscored rather than estimated until that data is indexed.
Impact—
Impact cannot be scored: the snapshot contains no citation counts, h-index, or downstream-adoption signals for these papers. The axis would measure the citation-based influence of the work, and it remains unscored rather than estimated from the two cataloged preprints.
Focus0/100
The focus axis scores 0, reflecting an even 0.5/0.5 split in the field distribution between two distinct sub-fields: LLM benchmarking for network protocol analysis and cultural NLP. Within this two-paper snapshot the breadth looks deliberate, with the 2026 papers at opposite ends of applied NLP. Because only two papers are recorded, the score measures topical concentration on a very small base and may shift as more output is indexed.
Collaboration44/100
Collaboration scores 44, built on eight distinct co-authors recorded in the snapshot: Anqi Chen, Cristina Nita-Rotaru, Tania Chakraborty, Eylon Caplan, Zhaoqing Wu, Kevin Cushing, Han Qin, and Shreya Havaldar. Neither cataloged paper flags him as corresponding author — last position on CultureMINE and a middle position on RFCLLM — consistent with a mid-size team pattern rather than a large lab-scale network.
Activity—
Activity data is missing: no per-year publication cadence or recent-output trend is available beyond the two 2026 preprints. This axis would measure publishing rhythm over time, and it is left unscored until a longer indexed window exists.
Reproducibility78/100
Reproducibility is the strongest measured axis at 78, averaged over the two papers assessed in the catalog. RFCLLM is rated high readiness: a credible benchmark, though Evolve notes single-annotator gold answers and judge overlap temper trust. CultureMINE is rated medium, with annotation reliability unquantified. The pattern points to artifact-releasing benchmark and resource work with documented methodological caveats.
Research summary
Dan Goldwasser is a natural language processing researcher at the University of Pennsylvania whose cataloged work spans two distinct sub-fields: cultural NLP and LLM benchmarking for network protocol analysis. The Evolve catalog holds two 2026 arXiv papers, splitting his recorded field distribution evenly at 0.5 each. As last author on CultureMINE, he is attached to a survey of more than 375 cultural NLP papers that proposes a nine-capability taxonomy and observes that data work currently outpaces systems work, while annotation reliability remains unquantified. On RFCLLM he holds a middle authorship position on a benchmark testing whether LLMs can reason over network protocol finite state machines specified in RFCs; the headline finding is that models struggle even when gold FSMs are provided. Neither paper lists him as corresponding author. Reproducibility is the strongest measured dimension: the two assessed papers average 78, with RFCLLM rated high and CultureMINE medium readiness. Collaboration scores 44 against eight distinct co-authors. Output, impact, and activity metrics are absent from the underlying bibliometric snapshot, so those axes remain unscored.
Collaboration pattern
The snapshot records eight distinct co-authors — Anqi Chen, Cristina Nita-Rotaru, Tania Chakraborty, Eylon Caplan, Zhaoqing Wu, Kevin Cushing, Han Qin, and Shreya Havaldar — supporting a collaboration score of 44. Neither cataloged paper lists him as corresponding author: last position on CultureMINE, middle on RFCLLM. The co-author set spans both research fronts, suggesting small-to-mid-size team science across cultural NLP and protocol-analysis benchmarking rather than a single large lab cluster.
Research keywords
Highlights
Mapping cultural capabilities: a >375-paper survey of cultural NLP
RFCLLM: testing whether LLMs can reason over protocol state machines
Timeline
- 2026CultureMINE released on arXiv: a survey of more than 375 cultural NLP papers introducing a nine-capability taxonomy, with Goldwasser as last author.
- 2026RFCLLM released on arXiv: benchmarking LLM reasoning over network protocol finite state machines derived from RFC specifications; rated high reproducibility readiness.
- 2026Field distribution in the bibliometric snapshot splits evenly (0.5/0.5) between cultural NLP and protocol-analysis benchmarking, defining a two-front research profile.
- 2026Both papers enter the Evolve catalog, yielding a mean reproducibility score of 78 across the two assessed papers, with eight distinct co-authors recorded.
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 scores come from a limited snapshot: output, impact, and activity axes lack underlying data and are not scored.
- Only two papers (both 2026 arXiv preprints) are covered here; peer-reviewed venue records are not reflected in the input data.
- Profile is name-resolved from public bibliographic data tied to ORCID 0000-0001-9326-8601; same-name researchers outside this record are not covered.
- The focus score of 0 derives from a 50/50 split across two sub-fields in a two-paper snapshot and may shift as more output is indexed.