The paper investigates how different representations of Korean constituency structure affect parsing performance. It compares three formats—Morpheme+XPOS, Eojeol+XPOS, and Eojeol+UPOS—derived from the Penn Korean Treebank, using gold segmentation and labels to evaluate transition-based parsers. Results show that fine-grained morphological and XPOS information yields the best parsing accuracy, while eojeol-based representations offer shorter transition sequences but lower performance when only UPOS is used.
By Jungyeul Park, KyungTae Lim, Zihao Huang, Eunkyul Leah Jo, Yige Chen, Chulwoo Park
This article tackles an important phenomenon in the syntax of Yemeni Ibbi Arabic (YIA), viz. , wh-agreement, a phenomenon common to several languages including Greek, Indonesian, Lubukusu, Irish, etc.
The paper investigates Japanese past‑tense verb inflection in neural morphological generation systems, focusing on a rare irregular subtype where stems end in /e/ and require gemination before the suffix. Despite overall high accuracy (>97%), this <1% subclass accounts for 30–43% of residual errors, amplifying its impact by 34–48 times its frequency. Ablation experiments show that removing this specific subtype yields larger accuracy gains than removing all irregular verbs, highlighting the role of low‑frequency patterns and orthographic processes in error concentration.
By Wen Zhang
KoNeoBench is a curated dataset designed to evaluate large language models’ understanding of Korean neologisms. It contains 1,785 recently attested Korean words from online news since 2020, each accompanied by usage examples, word‑formation analyses, and dictionary‑style definitions. The authors define four evaluation tasks, report results from recent models and a human baseline, and find that current LLMs struggle with recovering source components, distinguishing semantic categories, and generating accurate definitions.
By Soha Lee, Soojin Lee, Heesung Yang, Hyunju Song, Hyunji Lee, Jinsan An, Jeongwan Shin, Jin Hyun Park, Jun Lee, Hyeyoung Park, Kilim Nam
arXiv:2608.28986v1 Announce Type: new
Abstract: LLMs often struggle with modern Korean poetry, producing outputs that resemble "line-broken prose." We address two coupled tasks: detecting whether a K...
By Keunhyeung Park, Seunguk Yu, YoungBin Kim
arXiv:2606. 15144v1 Announce Type: cross Abstract: Large language models (LLMs) process text as sequences of subword tokens, which can obscure the character-level and morphological structure that underlies word formation.
By Jann Railey Montalan, David Demitri Africa, Jimson Paulo Layacan, Richell Isaiah Flores, Ivan Yuri De Leon, Lance Calvin Gamboa
The article examines how Byte‑Pair Encoding (BPE) tokenization handles Polish, an inflectional language, and finds that BPE tends to stabilize frequent surface fragments of grammatical exponents rather than true grammatical categories. It introduces the concept of grammatical form anchoring, showing that certain Polish verb forms can signal the speaking subject without an explicit pronoun, and highlights that language models may lack a stable grammatical "I" and can shift gender or mirror user forms. The study proposes Roclawski’s segmentation‑flexional forms as a diagnostic framework and suggests that more stable Polish modeling would require sublexical stabilization, anchoring grammatical form in the inflectional system, and maintaining the grammatical "I" in dialogue.
By Elzbieta Dawidek (University of Lower Silesia DSW Ideis)
arXiv:2607. 18961v1 Announce Type: new Abstract: Large language models (LLMs) generate fluent text by incrementally predicting the next token from a prefix.
By Remo Pareschi
arXiv:2302.00129v2 Announce Type: replace
Abstract: Despite their widespread use, the principles governing the organisation of syntactic dependency trees remain poorly understood. I analyse dependenc...
By Ferm\'in Moscoso del Prado Mart\'in
The paper studies how transformer representations evolve across layers by examining the intrinsic dimensionality (ID) of token embeddings and their neighborhood structures. It finds that closed‑class tokens expand and collapse earlier than open‑class tokens, and that these changes are linked to shifts in local geometry. The authors compare encoder and decoder models, showing distinct layer‑wise behaviors, and demonstrate that geometric features alone can predict a token’s part‑of‑speech and reveal how semantic content changes across layers.
By Samuele Vallisa, Federico Ravenda, Claudio Palominos, Rui He, Andrea Raballo, Antonietta Mira, Philipp Homan, Wolfram Hinzen
arXiv:2608. 00523v2 Announce Type: replace-cross Abstract: The linguistic notion of state has traditionally been restricted to the construct (annexation) state of Afroasiatic languages and treated as a language-specific morphosyntactic phenomenon.
By Mohamed El Idrissi
The paper introduces the Fixed Suffix Dependency Ratio (FSDR) as a metric to measure how much loanwords depend on fixed derivational suffixes for gender assignment. Analyzing 1,832 Latvian noun lemmas, it finds that feminine loanwords rely more on fixed suffixes while masculine loanwords are largely free‑choice, a pattern that has intensified in recent usage. FSDR offers a quantitative tool for distinguishing morphological anchoring from default gender in language contact scenarios.
By Yelingyun Zhang, Atis Kapenieks, Marina Platonova