fundamental limitations
Fundamental limitations in AI refer to the inherent restrictions of algorithms and models regarding what they can learn or achieve. Understanding these limitations is crucial for setting realistic expectations and guiding research directions.
- Absence Bench: Language Models Can’t See What’s Missing
- BREAD: Branched Rollouts from Expert Anchors Bridge SFT & RL for Reasoning
- LTD-Bench: Evaluating Large Language Models by Letting Them Draw
- Regional Explanations: Bridging Local and Global Variable Importance
- Understanding Prompt Tuning and In-Context Learning via Meta-Learning