From Early Encoding to Late Suppression: Interpreting LLMs on Character Counting Tasks
From Early Encoding to Late Suppression: Interpreting LLMs on Character Counting Tasks explores Interpreting LLM failures on character counting tasks to reveal internal reasoning and output suppression mechanisms.. Commercial viability score: 4/10 in LLM Interpretability.
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 $10K - $14K 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 ThisCan LLMs Model Incorrect Student Reasoning? A Case Study on Distractor GenerationViability: 3.0
- Prior WorkSame Meaning, Different Scores: Lexical and Syntactic Sensitivity in LLM EvaluationViability: 4.0
- Prior WorkThe Diminishing Returns of Early-Exit Decoding in Modern LLMsViability: 4.0
- Higher ViabilityFragile Reasoning: A Mechanistic Analysis of LLM Sensitivity to Meaning-Preserving PerturbationsViability: 7.0
- Higher ViabilityLLMs Encode Their Failures: Predicting Success from Pre-Generation Activations