dimension_forced

"We train our model in an end-to-end manner on massive multi-view data containing around 1 million objects, including both synthetic renderings from Objaverse and real captures from MVImgNet."

"Our team at Meta Reality Labs Research built the Project Aria device, an egocentric, multi-modal data recording and streaming device with the goal to foster and accelerate research in this area. In this paper, we describe the Project Aria device hardware including its sensor configuration and the corresponding software tools"

"Extensive experiments on the NAVSIM and Bench2Drive benchmarks demonstrate that ReCogDrive achieves state-of-the-art performance."

"Jurassic-X... some of the technical challenges in implementing it"

"Across a wide range of sampling step budgets, shortcut models consistently produce higher quality samples than previous approaches, such as consistency models and reflow."

"We have carefully considered the potential ethical implications of releasing this benchmark, and believe that it will be a net positive for the community."

"We introduce MMMU: a new benchmark designed to evaluate multimodal models on massive multi-discipline tasks demanding college-level subject knowledge and deliberate reasoning. MMMU includes 11.5K meticulously collected multimodal questions from college exams, quizzes, and textbooks, covering six core disciplines..."

"Key techniques such as long data synthesis, progressive pre-training, and multi-stage supervised fine-tuning are employed to effectively enhance long-context performance while reducing training costs."

"LiveBench contains questions that are based on recently-released math competitions, arXiv papers, news articles, and datasets, and it contains harder, contamination-limited versions of tasks from previous benchmarks such as Big-Bench Hard, AMPS, and IFEval."

"AF3 achieves new SOTA results on over 20+ (long) audio understanding and reasoning benchmarks"

"MDM is a generic approach, enabling different modes of conditioning, and different generation tasks. We show that our model is trained with lightweight resources and yet achieves state-of-the-art results on leading benchmarks for text-to-motion and action-to-motion."

"comprehensive evaluations on nearly 20 benchmarks show that Thyme yields significant and consistent performance gains, particularly in challenging high-resolution perception and complex reasoning tasks"

"These discordances primarily rest on the divergence in the measurement of core cosmological parameters with varying levels of statistical confidence. These possible statistical tensions may be partially accounted for by systematics in various measurements or cosmological probes but there is also a growing indication of potential new physics beyond the standard model."

"We introduce spotlighting, a family of prompt engineering techniques"

"Our OpenVid-1M has several characteristics: 1) Superior in quantity... 2) Superior in visual quality... 3) Expressive in caption"

"their persistence after several years of accurate analysis strongly hints at cracks in the standard cosmological scenario and the necessity for new physics or generalisations beyond the standard model"

"Our training data for phi-1.5 is a combination of phi-1’s training data (7B tokens) and newly created synthetic, “textbook-like” data (roughly 20B tokens) for the purpose of teaching common sense reasoning and general knowledge of the world"

"establish new state-of-the-art results on five related benchmarks - WSC (90.1%), DPR (93.1%), COPA (90.6%), KnowRef (85.6%), and Winogender (97.1%)"

"Assuming baryon number conservation, we find 15 + 19 + 25 = 59 independent operators (barring flavour structure and Hermitian conjugations), as compared to 16 + 35 + 29 = 80 in Ref.[3]."

"HuggingGPT can tackle a wide range of sophisticated AI tasks spanning different modalities and domains"

"We report a Hubble constant of H0=66.66±0.60 km/s/Mpc from SPT-3G alone, 6.2 sigma away from local measurements from SH0ES."

"ReTool-32B attains 72.5% accuracy... outperforming OpenAI's o1-preview by 27.9%"

"On CALVIN benchmark, our method outperforms state-of-the-art baseline methods and improves the success rate from 88.9% to 94.9%."

"We find no evidence for excess lensing in the power spectrum, and no departure from spatial flatness."

"We scale our models as large as 14 billion parameters, by far the largest dense RNN ever trained, and find RWKV performs on par with similarly sized Transformers."

"MTL acts as a regularizer by introducing an inductive bias. As such, it reduces the risk of overfitting as well as the Rademacher complexity of the model."

"Theoretical ideas to explain the discrepancy focused on new physics in the decade of expansion preceding recombination"

"Building upon our scalable super-computing infrastructure and the classical transformer architecture"

"We present a polynomial quantum algorithm for the Abelian stabilizer problem which includes both factoring and the discrete logarithm. Our method is based on a procedure for measuring an eigenvalue of a unitary operator."

"decoupling of variables in the perturbation equations, quasinormal modes (with special emphasis on various numerical and analytical methods of calculations), late-time tails, gravitational stability"