ONTOTEXT (From Text to Knowledge for the Semantic Web)

Oct 1, 2004 | Projects

1 October 2004 to 30 September 2007 - PROJECT CLOSED

Based on the philosophy of the Semantic Web, Ontotext exploits text processing and automatic reasoning technologies to extract knowledge from texts and organise it conceptually in an ontology. Unlike common search engines, the Ontotext Portal directly accesses the concepts and entities of the ontology and presents the user with structured information instead of mere portions of texts. For each entity, the Ontotext Portal offers four different views: Articles (lists all the documents in which it is mentioned), Citografo (shows how often it is mentioned), Opinions (shows how often opinions are expressed about it), and Record (provides extra information about it).

MT Group at FBK Follow

#MachineTranslation Research Unit @FBK_research. #nlproc #deeplearning #ai

Avatar MT Group at FBK @fbk_mt ·

24 Jul

Our pick of the week by
@mgaido91

: "FlexiSLM: A Dynamic and Controllable Frame Rate Spoken Language Model" by Jiaqi Li, Chaoren Wang, Xiaohai Tian, Mingjie Chen, Xinyu Liang, Xu Li, Yufan Lin, Junwen Qiu, Jun Zhang, Lu Lu, Haizhou Li and @drwuz
#SLM #EfficientInference

Marco Gaido @mgaido91

Cool to see a work that adaptively chooses at inference how much to compress the input speech sequence, to control inference costs and quality based on the input, without enforcing a global trade-off to each segment: https://arxiv.org/pdf/2606.31247

@fbk_mt

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Avatar MT Group at FBK @fbk_mt ·

8 Jul

Our pick of the week by
@FBKZhihangXie : "Speech-XL: Towards Long-Form Speech Understanding in Large Speech Language Models" by Haoqin Sun, @Chenyang_Lyu, Shiwan Zhao, Xuanfan Ni, Xiangyu Kong, @wangly0229, Weihua Luo and Yong Qin
#SpeechLLM #LongFormSpeech #SLU

Zhihang Xie @FBKZhihangXie

🚀 New paper: Speech-XL for long-form SpeechLLMs
📄 https://arxiv.org/abs/2602.05373
🧩 Uses Speech Summarization Tokens to compress local speech intervals into compact KV states efficiently.
✨ Improves long-form speech understanding while reducing memory and FLOPs on 10-minute audio.

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Avatar MT Group at FBK @fbk_mt ·

25 Jun

Last week, we had a great talk for our MT Seminar Series!
@julius_gulius a PhD from @cambridgenlp presented a talk on "Effective uses of grammatical knowledge in extremely low-resource Machine Translation"
#MachineTranslation #LowResourceMT #NLProc #FBK

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24 Jun

Our pick of the week by
@BeatriceSavoldi
: "Accuracy: Community Perspectives on Machine Translation" by Yujun Wang,
@EhudReiter
, Shimei Pan,
@egere14
and Wei Zhao #MachineTranslation #TranslationQuality #Evaluation

BeatriceSavoldi @BeatriceSavoldi

📖 #PickoftheWeek @fbk_mt "Accuracy: Community Perspectives on Machine Translation"

A cool analysis of the conflicting interests of different communities around MT(AI developers, LSPs, and users)
https://arxiv.org/pdf/2606.09655
#NLP #MachineTranslation #DiverseStakeholders

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