Trace out-of-home ad claims from claim extraction through evidence linking to an overall fact-review conclusion.

Train models to detect conflicts across sources and judge whether citations adequately support synthetic social advertising claims.

This dataset focuses on speech recognition tasks for academic lecture scenarios.

Train code models on practical mobile shooter scenarios involving touch controls, aiming, and firing interactions.

Link news claims to their sources and supporting evidence so models can preserve reporting differences without deciding which account is true.

Help models detect outdated citations and evidence by testing whether social ad claims align with their sources over time.

Train models to turn requirements for filter appearance, scenes, and interactions into JavaScript code for AR social filters.

Train on practical Lua and Luau completion examples for core ad and in-app purchase flows in mobile casual games.

Train models to spot outdated or inapplicable social media ad claims with structured temporal, geographic, availability, and evidence checks.

Use synthetic recommendation copy and structured evidence labels to detect when personal experiences are improperly presented as universal facts.

Train precise citation coverage and completeness checks with synthetic social ads and structured evidence annotations.

Extract source-grounded developments and timelines from international news reports while keeping cross-report differences explicit.

Test whether video ad script reward validators can catch rule boundaries and evasion attempts with challenging compliant and near-miss pairs.

Ground professional music licensing Q&A and key clause analysis in the contract text.

Connect breaking-news claims with webpage evidence and verdicts to support traceable, evidence-based fact-checking.

Test whether numerical claims in social ads are genuinely supported by citations with explicit metric definitions and conditions.

Examine comparative ad claims with structured evidence, qualifying conditions, and traceable fact-check labels.

Generate video ad copy grounded in product facts and evaluate it with verifiable measures of required-fact retention and unsupported claims.

Extract structured events from international news and trace key attributes back to evidence in the source text.

Train models to generate clearly structured advertising text for outdoor media using verifiable layout constraints across multiple display formats.