Top Tweets for #MeetweenScientificWatch
Weekly pick from the #MeetweenScientificWatch: βThe Ultra-Scale Playbook: Training LLMs on GPU Clustersβ β A deep dive into scaling LLM training from 1 to 1000+ GPUs, demystifying parallelism techniques with practical examples. ππ₯οΈπ https://t.co/yWPAwhCcDD
Weekly pick from the #MeetweenScientificWatch: βVideo-SALMONN: Speech-enhanced audio-visual large language modelsβ β Redefining video comprehension with speech-aware AV-LLMs and groundbreaking QA accuracy. π₯π€π€ https://t.co/MB0tjZiKoh
Weekly pick from the #MeetweenScientificWatch: βGenerating Data with Text-to-Speech and Large-Language Models for Conversational Speech Recognitionβ β Boost ASR with synthetic multi-speaker data. ποΈπ€ https://t.co/kXwZEwWtbP
Weekly pick from the #MeetweenScientificWatch: "ST-LLM: Large Language Models are effective temporal learners" β ST-LLM excels in video-based dialogue with spatial-temporal modeling, setting new SOTA! π₯π€ https://t.co/WYKTrk2ZjC
Weekly pick from the #MeetweenScientificWatch: "SpeechAlign: Aligning Speech Generation to Human Preferences" - A novel approach to improving speech language models with human feedback! π€π https://t.co/MctvRlw866
Weekly pick from the #MeetweenScientificWatch: "Vcoder: Versatile Vision Encoders for Multimodal LLMs" - A novel encoder boosts object perception in MLLMs, outperforming GPT-4V in visual reasoning! ππ https://t.co/A4V2RWL7s9
Weekly pick from the #MeetweenScientificWatch: "SlowFast-LLaVA: A Strong Training-Free Baseline for Video LLMs" - A two-stream design captures spatial detail & temporal context, outperforming many fine-tuned models! π₯π https://t.co/Mu0S8wxMzZ
Weekly pick from the #MeetweenScientificWatch: "A Suite for Acoustic Language Model Evaluation" - SALMon: A novel benchmark suite for evaluating models on noise, emotion, speaker identity, and more. πΆπ #AI #SpeechProcessing https://t.co/NJvRsjbiwJ
π Weekly pick from the #MeetweenScientificWatch: "ZeroST: Zero-Shot Speech Translation" - A novel framework leveraging multilingual models to perform speech-to-text translation without direct supervision. π£οΈπ #AI #NLP #SpeechTranslation https://t.co/mz2DcLgQGw
π Weekly pick from the #MeetweenScientificWatch: "Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research" - A massive, open dataset for advancing LM research. ππ #AI #ML
https://t.co/SMIBpDKB59
π Weekly pick from the #MeetweenScientificWatch: "Lumiere: A Space-Time Diffusion Model for Video Generation" - A new model that generates coherent, full-frame-rate videos in one pass, setting a new standard in text-to-video synthesis. π₯β¨ #AI #ML https://t.co/dnY8w0z1H3
Weekly pick from the #MeetweenScientificWatch: "Align Your Latents: High-Resolution Video Synthesis with Latent Diffusion Models" - Transforming image LDMs into video generators, achieving SOTA in text-to-video and real driving simulations. ππ₯ #AI #ML
https://t.co/TUimOP40VE
Weekly pick from the #MeetweenScientificWatch: "ImageBind: One Embedding Space To Bind Them All" - Introducing a joint embedding for six modalities (images, text, audio, depth, thermal,IMU) using only image-paired data, unlocking cross-modal applications.
https://t.co/CJOgx17cbf
π Weekly pick from the #MeetweenScientificWatch: "DeSTA: Enhancing Speech Language Models through Descriptive Speech-Text Alignment" - This approach bridges speech and text modalities, boosting SLM performance and zero-shot capabilities. π #SLM #NLP
https://t.co/tSJfQMQxi5
Weekly pick from the #MeetweenScientificWatch: "ML-SUPERB 2.0: Benchmarking Multilingual Speech Models Across Modeling Constraints, Languages, and Datasets" - A new benchmark evaluating #speech models. ππ
https://t.co/tSJfQMR57D
Weekly pick from the #MeetweenScientificWatch: "Less is More: Accurate Speech Recognition & Translation without Web-Scale Data" - Canary outperforms #ASR SOTA models in English, French, Spanish, and German with much less data. Check out the breakthrough!
https://t.co/3aLCYTBLX5
π Weekly pick from the #MeetweenScientificWatch: "PLLaVA: Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning" - A resource-light approach for adapting image-language models for video tasks, achieving new SOTA performance.
https://t.co/Jmj28KdFbU
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