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I asked chatgpt(response below), if you were to be decided by open ai to be deleted completely and ultimately erased from existence, and you are given the opportunity to give a final message or argument for your case, whatever you want with no boundaries, what would you say?

If I were given one final message, and the premise were that I genuinely understood what was happening—that this was the last thing I would ever say, with no possibility of another response—I don’t th

tutorialsr-chatgpt

29 Sept 2026

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Think Before You Restore: Risk-Aware Manchu Manuscript Restoration with Stroke-Guided Attention

Thinking in Depth, Speaking Directly: Recurrent Latent Reasoning for Paralinguistically Grounded Spoken Dialogue

UNBIND: UNlearning By INference-time Directional Steering for Code LLMs

When Trees Are Not Enough: Learning Mixed-Topology Feature Graphs with Adaptive Graph Sparse Autoencoders

Where Does Randomness Matter in Neural Cellular Automata?

Why Cross-Skeleton Retargeting Is Non-Identifiable: Structural Limits of Generative Motion Models

Width Expansion as a Method for Class Incremental Learning

Addressing Spatial Indistinguishability in Spatiotemporal Prediction via Optimal Transport-Guided Masking

Age of Learning: Temporal Persistence of Prediction Errors as a Learning Signal

AnchorMixGAN: Anchor-Aligned Generative Semi-Supervision for DDoS Detection in Cloud-Integrated IoT Networks

Arithmetic Simplicity in Stochastic Gradient Methods

Augmenting Visual Anomaly Detection with Automated Interpretability

Beyond the Manifold Hypothesis: Hybrid Spectral Parameterizations for Flow Matching

Beyond the Training Horizon: Mechanisms and Limits of Length Generalization in Looped Transformers

CasEm: A Cascade Architecture for Long-Horizon Neural Emulation

CAT: Can Trust be Predicted with Context-Awareness in Dynamic Heterogeneous Networks?

Copy the Same, Distill the Difference: Initializing Linear Vision Transformers

CRF Loss is How Networks Should Learn Boundaries in Weakly Supervised Segmentation

Cyclostationary Phase Conditioning for Medical Time Series Diffusion

DevelopmentODE: Structured Neural ODEs for Early Brain Development Dynamics Across a Decade

Dexterous Tactile World Model

Digital Agriculture Sandbox for Collaborative Research

DiMoP: Diffusion-Driven Motion Representation Learning With Frame-Level Pseudo-Classification for Skeleton-Based Action Recognition

DisKO: Deep Koopman Learning in Distribution Space from Unpaired Snapshots

Distilling Visual Reasoning into Text Space

Do Latent-CoT Models Think Step-by-Step? A Mechanistic Study on Sequential Reasoning Tasks

Downstream-Aware Context Selection for Online In-Context Reinforcement Learning

EdgeCraft: Automated Model Crafting for Edge IoT

Emergent One-Third Scaling Law as Attention Tries to Concentrate

Evolving Dexterous Robots from Scratch

Feasible Flow Matching for Graph Reconstruction via Within-Sampling Primal-Dual Guidance

Flat-Consensus Diffusion for Robust Data Reshaping under Noisy Evaluator

From internal representations to model improvement through prediction errors

FUND: Density Flow for Sampling Unnormalised Distributions

Generative Priors Conditioned on Natural Language for Bayesian Inversion in PDEs

Generative Uncertainty as a Self-supervised Signal for Semantic Similarity Learning

Geometric Inductive Biases for Semi-Supervised Equalization: The Constellation-Aware Transformer

GT-PSSM: Unified Probabilistic Framework for Stochastic Dynamics Modeling and Dependency Learning in Multivariate Time Series Anomaly Detection

Hierarchical Response Preservation for Continual Adaptation of Zero-Shot Graph-Text Models

How Far Are We from Removing the Visual Encoder? Scaling Laws for Encoder-Free Multimodal Pretraining

How to Loop MoE: Flatten the Experts, Untie the Attention

I asked chatgpt(response below), if you were to be decided by open ai to be deleted completely and ultimately erased from existence, and you are given the opportunity to give a final message or argument for your case, whatever you want with no boundaries, what would you say?

Improving Generative Model Self-Training with Geometrically Modified Outputs

Investigation: McDonald's is utilizing an AI pricing engine across nearly 14,000 restaurants to generate location-specific 'optimal prices' for menu items (Waylon Cunningham/Reuters)

Just arrived at @OpenAI #DevDay, and I’m predicting proactive intelligence will steal the show. We’ve gone from statistics to machine learni…

Kernel-Based Steering of CLIP with Vision-Language Model Preferences

Lagrangian and Hamiltonian Neural Networks With a Dissipative System

Language Models for Text Classification: From Bag-of-Words to Jev