# What are the Goals of Distributional Semantics?

arXiv: https://arxiv.org/abs/2005.02982 · HTML: https://mlsanity.com/paper/2005.02982/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 May 2020.

## Built on by (most cited first, 8 of 8)

- [Word Acquisition in Neural Language Models](https://mlsanity.com/paper/2110.02406/) (2021)
- [Explainable Semantic Space by Grounding Language to Vision with Cross-Modal Contrastive Learning](https://mlsanity.com/paper/2111.07180/) (2021)
- [Language Models, Graph Searching, and Supervision Adulteration: When More Supervision is Less and How to Make More More](https://mlsanity.com/paper/2503.10542/) (2025)
- [Signal in Noise: Exploring Meaning Encoded in Random Character Sequences with Character-Aware Language Models](https://mlsanity.com/paper/2203.07911/) (2022)
- [Learning Functional Distributional Semantics with Visual Data](https://mlsanity.com/paper/2204.10624/) (2022)
- [Agentivit`a e telicit`a in GilBERTo: implicazioni cognitive](https://mlsanity.com/paper/2307.02910/) (2023)
- [Using dependency parsing for few-shot learning in distributional semantics](https://mlsanity.com/paper/2205.06168/) (2022)
- [Empirical Sufficiency Lower Bounds for Language Modeling with Locally-Bootstrapped Semantic Structures](https://mlsanity.com/paper/2305.18915/) (2023)

## Abstract (arXiv)

Distributional semantic models have become a mainstay in NLP, providing useful features for downstream tasks. However, assessing long-term progress requires explicit long-term goals. In this paper, I take a broad linguistic perspective, looking at how well current models can deal with various semantic challenges. Given stark differences between models proposed in different subfields, a broad perspective is needed to see how we could integrate them. I conclude that, while linguistic insights can guide the design of model architectures, future progress will require balancing the often conflicting demands of linguistic expressiveness and computational tractability.