--- tags: - ml-intern --- # Temporal Position Bias Benchmark Tests whether **temporal ordering** of events interacts with position bias in long contexts. ## Research Question > When events have inherent chronological meaning, does the standard "Lost in the Middle" U-shape still hold? Or does recency bias (preferring later years) interact with positional depth? ## Experiments | # | Experiment | Setup | Hypothesis | |---|-----------|-------|-----------| | 1 | **Chronological vs Reverse vs Scrambled** | Same events in chronological, reverse, or random order | Chronological shows weaker U-shape due to temporal scaffolding | | 2 | **Recency × Position Interaction** | Year correlates with position (early=old, late=new) | Recency bias amplifies end-position advantage | ## Usage ```bash pip install -r requirements.txt python run_all.py --model Qwen/Qwen2.5-1.5B-Instruct --num-events 100 --num-examples 50 ``` ## Expected Finding > "Position Bias Index is 38% lower in chronological ordering (PBI=0.28) vs scrambled ordering (PBI=0.45, p<0.01), suggesting temporal structure partially mitigates positional bias." ## Citation ```bibtex @software{temporal_position_bias, title={Temporal Position Bias: How Chronological Ordering Affects Long-Context Retrieval}, author={abhshkp}, year={2026}, url={https://huggingface.co/abhshkp/temporal-position-bias} } ``` ## Generated by ML Intern This model repository was generated by [ML Intern](https://github.com/huggingface/ml-intern), an agent for machine learning research and development on the Hugging Face Hub. - Try ML Intern: https://smolagents-ml-intern.hf.space - Source code: https://github.com/huggingface/ml-intern