The project EDAMOK (Enabling Distributed and Autonomous Management of Knowledge) aims at promoting a distributed approach to knowledge management, namely an approach based on the two following principles: (i) Principle of Autonomy: each organizational unit should be allowed a large degree of autonomy in managing (creating, representing, organizing, selecting, sharing) its own knowledge (βlocalβ knowledge); (ii) Principle of Coordination: knowledge sharing across organizational units should be thought of as a form of coordination between multiple autonomous perspectives rather than as a process of creating (and imposing) a supposedly shared knowledge structure. The goal of EDAMOK is to develop (i) a theoretical framework, a (ii) methodology, and (iii) a collection of technological tools to support this distributed and autonomous approach to knowledge management.
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
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
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
π New paper: Speech-XL for long-form SpeechLLMs
π https://arxiv.org/abs/2602.05373
π§© Uses Speech Summarization Tokens to compress local speech intervals into compact KV states efficiently.
β¨ Improves long-form speech understanding while reducing memory and FLOPs on 10-minute audio.
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
π #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