# Modeling Bottom-up Information Quality during Language Processing

arXiv: https://arxiv.org/abs/2509.17047 · HTML: https://mlsanity.com/paper/2509.17047/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 37 references that are in the map.
- First posted on arXiv 21 Sep 2025.

## Builds on (most cited first, 10 of 10)

- [Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution](https://mlsanity.com/paper/2409.12191/) (2024)
- [Information-Theoretic Probing for Linguistic Structure](https://mlsanity.com/paper/2004.03061/) (2020)
- [On the Effect of Anticipation on Reading Times](https://mlsanity.com/paper/2211.14301/) (2022)
- [STARC: Structured Annotations for Reading Comprehension](https://mlsanity.com/paper/2004.14797/) (2020)
- [Quantifying the redundancy between prosody and text](https://mlsanity.com/paper/2311.17233/) (2023)
- [Texture or Semantics? Vision-Language Models Get Lost in Font Recognition](https://mlsanity.com/paper/2503.23768/) (2025)
- [Disambiguatory Signals are Stronger in Word-initial Positions](https://mlsanity.com/paper/2102.02183/) (2021)
- [An information-theoretic model of shallow and deep language comprehension](https://mlsanity.com/paper/2405.08223/) (2024)
- [The time scale of redundancy between prosody and linguistic context](https://mlsanity.com/paper/2503.11630/) (2025)
- [Using Information Theory to Characterize Prosodic Typology: The Case of Tone, Pitch-Accent and Stress-Accent](https://mlsanity.com/paper/2505.07659/) (2025)

## Abstract (arXiv)

Contemporary theories model language processing as integrating both top-down expectations and bottom-up inputs. One major prediction of such models is that the quality of the bottom-up inputs modulates ease of processing -- noisy inputs should lead to difficult and effortful comprehension. We test this prediction in the domain of reading. First, we propose an information-theoretic operationalization for the "quality" of bottom-up information as the mutual information (MI) between visual information and word identity. We formalize this prediction in a mathematical model of reading as a Bayesian update. Second, we test our operationalization by comparing participants' reading times in conditions where words' information quality has been reduced, either by occluding their top or bottom half, with full words. We collect data in English and Chinese. We then use multimodal language models to estimate the mutual information between visual inputs and words. We use these data to estimate the specific effect of reduced information quality on reading times. Finally, we compare how information is distributed across visual forms. In English and Chinese, the upper half contains more information about word identity than the lower half. However, the asymmetry is more pronounced in English, a pattern which is reflected in the reading times.