AI@TN

Jan 1, 2022 | Projects

1 January 2022 to 31 December 2023 - PROJECT CLOSED

An investment by the Autonomous Province of Trento in young talents involved in projects in synergy between FBK and the University of Trento on common research and highly innovative technological development initiatives that will pave the way for market and societal impact. The research activities will take place in the 4 macro-areas of Integrative AI, AI at the edge, Certified AI, and Interactive AI.

MT Group at FBK Follow

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

Avatar MT Group at FBK @fbk_mt ·

10 Jun

Our pick of the week by
@lina_conti

: "Greater accessibility can amplify discrimination in generative AI" by
@CarolinHolterm, @minhducbui_nlp, @KaitlynZhou, @vjhofmann, @kelina1124, @anne_lauscher
📰
#GenderBias #SpeechLLM

Lina Conti @lina_conti

Pick of the week @fbk_mt: "Greater accessibility can amplify discrimination in generative AI"

Gender bias in speech-based LLMs examined from multiple angles: a user survey, automatic bias measurement, and pitch manipulation experiments.

https://arxiv.org/pdf/2603.22260

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Avatar MT Group at FBK @fbk_mt ·

9 Jun

Late update, but we had two great talks last month!

#MachineTranslation #FBK #NLProc #GenderBias #SpeechSynthesis

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Avatar MT Group at FBK @fbk_mt ·

3 Jun

Our pick of the week by @dhairya_su47605

: "Scaling Laws for Precision" by @tanishqkumar07, Zachary Ankner, @bfspectorShiekh, @blake__bordelon, @Muennighoff, @mansiege, @CPehlevan, Christopher R´e, @AdtRaghunathan

📰

#Quantization #LLM #ScalingLaw

Dhairya Suman @dhairya_su47605

Pick of the week @fbk_mt
Super interesting paper on the limitations of quantization, demonstrating how post-training quantization scales poorly in data.

https://arxiv.org/abs/2411.04330

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Avatar MT Group at FBK @fbk_mt ·

27 May

⭐ For our #PickOfTheWeek, this paper explores an important question for modern speech AI:

🎙️ Which Evaluation for Which Speech Model?
👥 Authors: @Maureendss , @EeshanDhekane

Speech foundation models are evolving rapidly, but evaluation practices are still fragmented.

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