Pith. sign in

REVIEW 6 cited by

Multi30K: Multilingual English-German Image Descriptions

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1605.00459 v1 pith:UJ3HINPC submitted 2016-05-02 cs.CL cs.CV

Multi30K: Multilingual English-German Image Descriptions

Desmond Elliott , Stella Frank , Khalil Sima'an , Lucia Specia This is my paper
classification cs.CL cs.CV
keywords descriptionsimagedatasetdescriptionenglishmultilingualdatamulti30k
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

We introduce the Multi30K dataset to stimulate multilingual multimodal research. Recent advances in image description have been demonstrated on English-language datasets almost exclusively, but image description should not be limited to English. This dataset extends the Flickr30K dataset with i) German translations created by professional translators over a subset of the English descriptions, and ii) descriptions crowdsourced independently of the original English descriptions. We outline how the data can be used for multilingual image description and multimodal machine translation, but we anticipate the data will be useful for a broader range of tasks.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 6 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. VIDA: A dataset for Visually Dependent Ambiguity in Multimodal Machine Translation

    cs.CL 2026-05 unverdicted novelty 7.0

    VIDA provides 2,500 visually-dependent ambiguous translation examples and span-level disambiguation metrics; CoT-SFT on LVLMs improves out-of-distribution performance over standard SFT.

  2. Decentralized Nonconvex Optimization under Heavy-Tailed Noise: Normalization and Optimal Convergence

    math.OC 2025-05 conditional novelty 7.0

    GT-NSGDm achieves the optimal non-asymptotic convergence rate O(1/T^{(p-1)/(3p-2)}) for decentralized nonconvex stochastic optimization under zero-mean heavy-tailed noise with p-th moment.

  3. Hindi Visual Genome: A Dataset for Multimodal English-to-Hindi Machine Translation

    cs.CL 2019-07 unverdicted novelty 7.0

    The paper releases the first multimodal English-Hindi machine translation dataset of 31,525 segments with images and a challenge test set of 1,400 segments selected via embedding similarity for image-resolvable ambiguities.

  4. Do Transformers Need Three Projections? Systematic Study of QKV Variants

    cs.LG 2026-06 conditional novelty 6.0

    Q-K=V projection sharing in transformers matches standard QKV performance with 50% KV cache reduction and combines with GQA/MQA for up to 96.9% reduction across vision and language tasks.

  5. VIDA: A dataset for Visually Dependent Ambiguity in Multimodal Machine Translation

    cs.CL 2026-05 unverdicted novelty 6.0

    VIDA provides 2,500 visually-dependent ambiguous MT instances and LLM-judge metrics; chain-of-thought SFT improves disambiguation accuracy over standard SFT, especially out-of-distribution.

  6. Video-guided Machine Translation with Global Video Context

    cs.CV 2026-04 unverdicted novelty 4.0

    A globally video-guided multimodal translation framework retrieves semantically related video segments with a vector database and applies attention mechanisms to improve subtitle translation accuracy in long videos.