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Related papers: Paraphrases do not explain word analogies

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Large Language Models (LLMs) have made significant advances in natural language processing, but their underlying mechanisms are often misunderstood. Despite exhibiting coherent answers and apparent reasoning behaviors, LLMs rely on…

Computation and Language · Computer Science 2024-08-05 Bo Zhou , Daniel Geißler , Paul Lukowicz

Benchmarks measure whether a model is correct. They do not measure whether a model is reliable. This distinction is largely academic for single-shot inference, but becomes critical for agentic AI systems, where a single rephrased prompt can…

Machine Learning · Computer Science 2026-01-13 Aaron R. Flouro , Shawn P. Chadwick

Three-dimensional trajectories, or the 3D position and rotation of objects over time, have been shown to encode key aspects of verb semantics (e.g., the meanings of roll vs. slide). However, most multimodal models in NLP use 2D images as…

Computer Vision and Pattern Recognition · Computer Science 2023-03-23 Dylan Ebert , Chen Sun , Ellie Pavlick

In this paper, I apply linguistic methods of analysis to non-linguistic data, chess plays, metaphorically equating one with the other and seeking analogies. Chess game notations are also a kind of text, and one can consider the records of…

Computation and Language · Computer Science 2024-07-30 Boris Orekhov

We investigate some basic questions about the interaction of regular and rational relations on words. The primary motivation comes from the study of logics for querying graph topology, which have recently found numerous applications. Such…

Formal Languages and Automata Theory · Computer Science 2019-03-14 Pablo Barcelo , Diego Figueira , Leonid Libkin

We propose a distributional theory of how hypernymy -- the ``is-a'' relation between general and specific concepts -- is encoded geometrically in language representations. Starting from the empirically verified assumption that words closer…

Computation and Language · Computer Science 2026-05-25 Andres Nava , Matthieu Wyart

Static word embeddings encode word associations, extensively utilized in downstream NLP tasks. Although prior studies have discussed the nature of such word associations in terms of biases and lexical regularities captured, the variation in…

Computation and Language · Computer Science 2020-12-16 Geetanjali Bihani , Julia Taylor Rayz

The rapid development of such natural language processing tasks as style transfer, paraphrase, and machine translation often calls for the use of semantic similarity metrics. In recent years a lot of methods to measure the semantic…

Computation and Language · Computer Science 2022-11-15 Ivan P. Yamshchikov , Viacheslav Shibaev , Nikolay Khlebnikov , Alexey Tikhonov

Sentences with gapping, such as Paul likes coffee and Mary tea, lack an overt predicate to indicate the relation between two or more arguments. Surface syntax representations of such sentences are often produced poorly by parsers, and even…

Computation and Language · Computer Science 2018-04-20 Sebastian Schuster , Joakim Nivre , Christopher D. Manning

Much of philosophical logic and all of philosophy of language make empirical claims about the vernacular natural language. They presume semantics under which `and' and `or' are related by the dually paired distributive and absorption laws.…

Computation and Language · Computer Science 2014-03-19 Arthur Merin

Understanding context-dependent variation in word meanings is a key aspect of human language comprehension supported by the lexicon. Lexicographic resources (e.g., WordNet) capture only some of this context-dependent variation; for example,…

Computation and Language · Computer Science 2020-10-27 Sathvik Nair , Mahesh Srinivasan , Stephan Meylan

Graph convolutions have gained popularity due to their ability to efficiently operate on data with an irregular geometric structure. However, graph convolutions cause over-smoothing, which refers to representations becoming more similar…

Machine Learning · Computer Science 2024-09-04 Andreas Roth

By representing words with probability densities rather than point vectors, probabilistic word embeddings can capture rich and interpretable semantic information and uncertainty. The uncertainty information can be particularly meaningful in…

Computation and Language · Computer Science 2018-04-30 Ben Athiwaratkun , Andrew Gordon Wilson

Previous works have demonstrated the effectiveness of utilising pre-trained sentence encoders based on their sentence representations for meaning comparison tasks. Though such representations are shown to capture hidden syntax structures,…

Computation and Language · Computer Science 2022-10-12 Qiwei Peng , David Weir , Julie Weeds

Natural language exhibits statistical dependencies at a wide range of scales. For instance, the mutual information between words in natural language decays like a power law with the temporal lag between them. However, many statistical…

Computation and Language · Computer Science 2019-12-17 Aakash Sarkar , Marc Howard

Word embeddings represent language vocabularies as clouds of $d$-dimensional points. We investigate how information is conveyed by the general shape of these clouds, instead of representing the semantic meaning of each token. Specifically,…

Computation and Language · Computer Science 2025-01-15 Ondřej Draganov , Steven Skiena

Idioms are unlike most phrases in two important ways. First, the words in an idiom have non-canonical meanings. Second, the non-canonical meanings of words in an idiom are contingent on the presence of other words in the idiom. Linguistic…

Computation and Language · Computer Science 2022-09-16 Michaela Socolof , Jackie Chi Kit Cheung , Michael Wagner , Timothy J. O'Donnell

Being inspired by the success of \texttt{word2vec} \citep{mikolov2013distributed} in capturing analogies, we study the conjecture that analogical relations can be represented by vector spaces. Unlike many previous works that focus on the…

Computation and Language · Computer Science 2020-10-27 Falcon Z. Dai

We prime-encode the natural numbers via recursive factorisation, iterated to the exponents, generating a corpus of planar rooted trees equivalently represented as Dyck words. This forms a deterministic text endowed with internal rules.…

Mathematical Physics · Physics 2025-12-02 Pierluigi Contucci , Claudio Giberti , Godwin Osabutey , Cecilia Vernia

We evaluate LLMs' language understanding capacities on simple inference tasks that most humans find trivial. Specifically, we target (i) grammatically-specified entailments, (ii) premises with evidential adverbs of uncertainty, and (iii)…

Computation and Language · Computer Science 2024-04-12 Victoria Basmov , Yoav Goldberg , Reut Tsarfaty