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🚨 New Article Making ChatGPT Follow Orders: Simple, Deterministic Constraints

In today's academic landscape, most generative outputs resemble a recursive plagiarism of lesser-known papers, recycled endlessly without genuine authorship.

🔗https://hackernoon.com/making-chatgpt-follow-orders-simple-deterministic-constraints

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Making ChatGPT Follow Orders: Simple, Deterministic Constraints | HackerNoon

Control ChatGPT outputs with a Protocol. A single enforcement header transforms generative models into deterministic executors, ensuring reproducibility

Agustin V. Startari

@agustinstartari@mastodon.social · yesterday

🚨 New Article Making ChatGPT Follow Orders: Simple, Deterministic Constraints

In today's academic landscape, most generative outputs resemble a recursive plagiarism of lesser-known papers, recycled endlessly without genuine authorship.

🔗https://hackernoon.com/making-chatgpt-follow-orders-simple-deterministic-constraints

Making ChatGPT Follow Orders: Simple, Deterministic Constraints | HackerNoon

Control ChatGPT outputs with a Protocol. A single enforcement header transforms generative models into deterministic executors, ensuring reproducibility

Humanities Channel and 1 other boosted

Agustin V. Startari

@agustinstartari@mastodon.social · 4 days ago

🚨 New Article Making ChatGPT Follow Orders: Simple, Deterministic Constraints

In today's academic landscape, most generative outputs resemble a recursive plagiarism of lesser-known papers, recycled endlessly without genuine authorship.

🔗https://hackernoon.com/making-chatgpt-follow-orders-simple-deterministic-constraints

Making ChatGPT Follow Orders: Simple, Deterministic Constraints | HackerNoon

Control ChatGPT outputs with a Protocol. A single enforcement header transforms generative models into deterministic executors, ensuring reproducibility

Agustin V. Startari

@agustinstartari@mastodon.social · 4 days ago

🚨 New Article Making ChatGPT Follow Orders: Simple, Deterministic Constraints

In today's academic landscape, most generative outputs resemble a recursive plagiarism of lesser-known papers, recycled endlessly without genuine authorship.

🔗https://hackernoon.com/making-chatgpt-follow-orders-simple-deterministic-constraints

Making ChatGPT Follow Orders: Simple, Deterministic Constraints | HackerNoon

Control ChatGPT outputs with a Protocol. A single enforcement header transforms generative models into deterministic executors, ensuring reproducibility

Humanities Channel and 1 other boosted

Agustin V. Startari

@agustinstartari@mastodon.social · 4 days ago

🚨 New Article Real-Time Detection of Authority-Bearing Constructions Under Strict Causal Masking

This defines a benchmark for real-time detection of authority-bearing constructions under strict causal masking, where models access only left context.

🔗https://zenodo.org/records/17465070

Zenodo

Real-Time Detection of Authority-Bearing Constructions Under Strict Causal Masking

This datasheet defines a benchmark for real-time detection of authority-bearing constructions under strict causal masking, where models access only left context. It measures how accurately and quickly a system identifies linguistic signals of authority without future tokens. Authority-bearing constructions are treated as Type-0 productions within a regla compilada, binding syntactic and operational constraints to decisions. Three hypotheses guide the study: a compact causal detector with an authority lexicon can achieve reliable precision at low latency; performance depends on construction family and register rather than sentiment; limited buffers can improve stability without breaking causality. Multilingual datasets (English, Spanish, optional French, German, Portuguese) include transcripts, hearings, and policy texts segmented into token streams. Tasks involve streaming span detection and stance classification, evaluated at multiple latency checkpoints and causal budgets (b ∈ {32, 64, 128}). Metrics cover streaming F1, AUCL, and stability index.Baselines (oracle, lexicon-only, sentiment) and strict no-lookahead validation ensure isolation of causal effects. The benchmark shows how form, not intent, governs real-time authority recognition, enabling evaluation of models for compliance and human-in-the-loop systems without right-context access. DOI Primary archive: https://doi.org/10.5281/zenodo.17465070 Secondary archive: https://doi.org/10.6084/m9.figshare.30465578 SSRN: Pending assignment (ETA: Q4 2025)

Agustin V. Startari

@agustinstartari@mastodon.social · 4 days ago

🚨 New Article Real-Time Detection of Authority-Bearing Constructions Under Strict Causal Masking

This defines a benchmark for real-time detection of authority-bearing constructions under strict causal masking, where models access only left context.

🔗https://zenodo.org/records/17465070

Zenodo

Real-Time Detection of Authority-Bearing Constructions Under Strict Causal Masking