Interpreting Negation in GPT-2: Layer- and Head-Level Causal Analysis
Interpreting Negation in GPT-2: Layer- and Head-Level Causal Analysis explores A causal analysis of GPT-2's handling of negation, revealing critical insights into its internal representations.. Commercial viability score: 4/10 in NLP.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisWhen Prohibitions Become Permissions: Auditing Negation Sensitivity in Language ModelsViability: 3.0
- Builds On ThisEroding the Truth-Default: A Causal Analysis of Human Susceptibility to Foundation Model Hallucinations and Disinformation in the WildViability: 3.0
- Builds On ThisRevisiting Real-Time Digging-In Effects: No Evidence from NP/Z Garden-PathsViability: 3.0
- Builds On ThisA Unified Assessment of the Poverty of the Stimulus Argument for Neural Language ModelsViability: 3.0
- Prior WorkVia Negativa for AI Alignment: Why Negative Constraints Are Structurally Superior to Positive Preferences
Related Resources
- How does PersianPunc contribute to NLP?(question)
- How does PersianPunc contribute to NLP?(question)
- How does PersianPunc contribute to NLP?(question)
- NLP – Use Cases(use_case)