Datasets:
Why a New Benchmark? — Gap Analysis
V5.15.h.3 artefact — JOT submission readiness.
One-page argumentative summary of why the public benchmarks reviewed in
related_benchmarks_comparison.mdcannot be substituted for mssense-eval-benchmark v1.1.
The simultaneous-properties argument
The problem of closed-vocabulary action trace generation for conversational RPA authoring is operationally defined by the joint satisfaction of four properties:
- The output vocabulary is a closed catalogue of typed actions tied to an executable runtime, organised by channel (WEB_DOM, EXCEL, DESKTOP_UIA, FILE_IO, CONTROL, MAIL, API_REST, DATABASE, …). A method's output must resolve in this catalogue or fail at runtime.
- The input is conversational, with possibly implicit references,
multi-turn ambiguity, and the requirement to decide between
generating, asking, validating, or closing the conversation
(
expected_decision ∈ {INVALID, VALID, UNDERSTOOD, QUESTION, THINKING, DONE}). - The expected output is a durable multi-step action trace, not a single tool call. Correctness propagates across step dependencies (variables produced and consumed, control-flow blocks, scoped contexts).
- The input modality covers text, voice transcript, screenshot, demo recording, and mixed combinations.
A public benchmark substitutes only if it satisfies all four. The audit
in related_benchmarks_comparison.md shows that none does.
The disjunction of partial substitutes
Each related corpus covers a strict subset:
- WONDERBREAD covers (4) and parts of (2) but lacks (1) (no closed RPA catalogue — its action trace is a low-level GUI event log) and lacks (3) in the typed-trace sense (its expected output is a free-form SOP).
- WorkArena / WorkArena++ cover (3) on web but neither (2) (single-task spec, no conversation) nor (4) (web-only) nor (1) (web HTML actions, not RPA platform actions).
- Mind2Web / Multimodal-Mind2Web cover (3) on web, (4) partially with screenshots, but neither (1) nor (2).
- WebArena / OSWorld cover live agent execution, not authoring of a persistent artefact — orthogonal to (3) as defined here.
- JSONSchemaBench / XGrammar cover only the schema layer; the manuscript Section 1 explicitly argues that schema validity is necessary but insufficient.
- Toolformer / ReAct / APIBench / AgentBench target single-step or short-sequence tool calling, not multi-step authoring of an executable trace.
- FlowMind / SmartFlow are the closest in spirit but release no public evaluation corpus — both papers report on proprietary internal datasets.
The disjunction of any subset of these still leaves at least one of (1)–(4) uncovered.
The reuse-and-extend argument
mssense does not ignore the existing corpora. The
mssense_public_creation_wonderbread_v1_full sub-corpus reuses
WONDERBREAD's intent + action trace + SOP fields after a documented
transformation pipeline (internal, not distributed). The transformation
maps WONDERBREAD's open-vocabulary GUI events to the closed RPA action
catalogue, attaching the canonical fields (task_family,
channel_family, expected_decision, oracle) that the manuscript's
evaluation requires.
This reuse demonstrates that we are not rebuilding from scratch what already exists — we are augmenting what exists with the missing labels and structure, and we are adding the internally-authored audit and validation cases that no public corpus contains.
What a reviewer should walk away with
The manuscript is not making the strong claim "no relevant public benchmark exists." It is making the precise claim "no public benchmark simultaneously satisfies the four properties that the proposed problem formally requires." The strong form is empirically falsifiable, the precise form is the actual contribution.
A reviewer convinced that one of WONDERBREAD / WorkArena / Mind2Web is
sufficient is invited to indicate which of the four properties they
contest. The table in related_benchmarks_comparison.md provides a
testable per-property verdict for each candidate.
Reference for the in-text paragraph
A drop-in paragraph for Section 2.6 of the manuscript is in
manuscript_section_2_6.md.