tion with {ChatGPT}}, AUTHOR = {Ansari, Navid and Babaei, Vahid and Najafpour, Mohammad Mahdi}, LANGUAGE = {eng}, ISSN = {1477-9226}, DOI = {10.1039/d3dt04178f}, PUBLISHER = {Royal Society of Chemistry} [...] {{\c C}o{\u g}alan, U{\u g}ur and Bemana, Mojtaba and Seidel, Hans-Peter and Myszkowski, Karol}, LANGUAGE = {eng}, ISSN = {0167-7055}, DOI = {10.1111/cgf.15051}, PUBLISHER = {Blackwell-Wiley}, ADDRESS = [...] in Virtual Reality}, AUTHOR = {Jim{\'e}nez Navarro, Daniel and Serrano, Ana and Malpica, Sandra}, LANGUAGE = {eng}, ISSN = {0178-2789}, DOI = {10.1007/s00371-024-03707-6}, PUBLISHER = {Springer International}
deterministic co-lex width of a regular language $\mathcal L$ is the smallest width of such a co-lex order, among all DFAs recognizing $\mathcal L$. Since languages of small co-lex width admit efficient [...] computing the co-lex width of a language is relevant in these applications. The paper introducing co-lex orders determined that the deterministic co-lex width $p$ of a language $\mathcal L$ can be computed [...] Width of a Regular Language}, AUTHOR = {Becker, Ruben and Cenzato, Davide and Kim, Sung-Hwan and Kociumaka, Tomasz and Kodric, Bojana and Policriti, Alberto and Prezza, Nicola}, LANGUAGE = {eng}, URL = {
{Efficient and Differentiable Combinatorial Optimization for Visual Computing}, AUTHOR = {Abbas, Ahmed}, LANGUAGE = {eng}, URL = {urn:nbn:de:bsz:291--ds-426550}, DOI = {10.22028/D291-42655}, SCHOOL = {Universit{\"a}t [...] Inherently Interpretable Deep Neural Networks for Image Classification}, AUTHOR = {B{\"o}hle, Moritz}, LANGUAGE = {eng}, URL = {urn:nbn:de:bsz:291--ds-421904}, DOI = {10.22028/D291-42190}, SCHOOL = {Universit{\"a}t [...] challenging setting on multimodal egocentric videos and propose an adaptation method for vision-language models to generalize on egocentric domain. Moreover, we study unimodal image recognition in an open-set
Transfer [Full set of software and data is available upon request] Software Semantic relatedness from Language resource For now see our previous release at www.d2.mpi-inf.mpg.de/nlp4vision. We will shortly add
Group Computational Biology RG1 Automation of Logic RG2 Network and Cloud Systems RG3 Multimodal Language Processing Home Institute Mission Address Executive Board Scientific Members of MPG Scientific Advisory [...] Group Computational Biology RG1 Automation of Logic RG2 Network and Cloud Systems RG3 Multimodal Language Processing Publications Algorithms & Complexity Computer Vision and Machine Learning Internet A
extraction. Relation extraction is the task of, given a semantic target relation and given a natural language corpus, extracting all pairs of entities in the corpus that stand in the target relation. For example
representation languages for enriching the data with meaning. More specifically, on the theoretical side we will study the syntax and semantics of the main ontology and rule-based languages. On the practical
statements on the complexity of query answering by considering different fragments of the SPARQL language, including the RDFS entailment regime, and the federated scenario. We implement an efficient method [...] LINK ] (more details) 6. Linguistic theories for text coverage estimation Scalar implicatures are language features thatimply the negation of stronger statements, e.g., “She was married twice” typically
image search over conventional text-based approaches. Approach Our method is based on statistical language models on unigram and bigram textual features. We use visual features in the form of object classes
Group Computational Biology RG1 Automation of Logic RG2 Network and Cloud Systems RG3 Multimodal Language Processing Home Institute Mission Address Executive Board Scientific Members of MPG Scientific Advisory [...] Group Computational Biology RG1 Automation of Logic RG2 Network and Cloud Systems RG3 Multimodal Language Processing Publications Algorithms & Complexity Computer Vision and Machine Learning Internet A
