Holodeck combines GPT-4 and Objaverse assets to generate diverse, semantically accurate 3D environments from text prompts, advancing scene diversity and layout realism.

Yue Yang, Fan-Yun Sun, Luca Weihs et al.

TAP4LLM enhances large-scale table reasoning by sampling, augmenting, and serializing data, achieving a 7.93% performance boost.

Yuan Sui, Jiaru Zou, Mengyu Zhou et al.

Math-Shepherd automatically constructs process supervision data, enabling step-by-step verification and reinforcement of LLMs without human annotations.

Peiyi Wang, Lei Li, Zhihong Shao et al.

CogAgent is an 18-billion-parameter visual language model that excels in GUI understanding and navigation, achieving state-of-the-art results on multiple VQA benchmarks.

Wenyi Hong, Weihan Wang, Qingsong Lv et al.

A DPP-analyzed stochastic block solver achieves ˜O((n²+nk^{ω−1})log(1/ε)) for dense systems.

Michał Dereziński, Jiaming Yang

Proposes post-hoc α hypothesis testing linking p-values and e-values, enabling data-dependent error control with guarantees.

Nick W. Koning

Proposes a reservoir computing-based model for intracellular ion dynamics, revealing ion gradients as dynamic information carriers.

Dipesh Niraula, Issam El Naqa, Jack Adam Tuszynski et al.

CBQ method achieves efficient low-bit quantization for LLMs via cross-block reconstruction and adaptive quantization techniques.

Xin Ding, Xiaoyu Liu, Zhijun Tu et al.

Proposes KMCGs-enhanced diffusion-based motion style transfer, supporting ten dance styles with improved content preservation and scalability.

Wenjie Yin, Yi Yu, Hang Yin et al.

Proposes CoPoNeRF, a unified framework for pose-free novel view synthesis with significant improvements over prior methods, achieving high-quality rendering without explicit camera poses.

Sunghwan Hong, Jaewoo Jung, Heeseong Shin et al.

Introduces optimal Sobolev norm convergence rates for infinite-dimensional vector-valued ridge regression, removing boundedness assumptions via tensor product interpolation spaces.

Zhu Li, Dimitri Meunier, Mattes Mollenhauer et al.

SGLang system leverages RadixAttention and compressed FSM to accelerate large language model programs, achieving up to 6.4× throughput increase.

Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie et al.

W.A.L.T employs causal encoding and window attention to achieve state-of-the-art photorealistic video generation at 512×896 resolution, 8 fps.

Agrim Gupta, Lijun Yu, Kihyuk Sohn et al.

Upscale-A-Video leverages latent diffusion with local-global strategies for temporally consistent video super-resolution, surpassing existing methods with detailed results.

Shangchen Zhou, Peiqing Yang, Jianyi Wang et al.

Proposes LLM360 framework, fully open-sourcing 7B models, training code, data, checkpoints, and analysis for transparency.

Zhengzhong Liu, Aurick Qiao, Willie Neiswanger et al.

DiffVL combines vision and language to scale soft body manipulation using differentiable physics.

Zhiao Huang, Feng Chen, Yewen Pu et al.

EQ-Bench assesses LLMs' emotional understanding via dialogue-based emotion intensity ratings, achieving a correlation of 0.97 with broad intelligence benchmarks.

Samuel J. Paech

Vary method scales vision vocabulary, achieving 78.2% ANLS on DocVQA and 36.2% on MMVet.

Haoran Wei, Lingyu Kong, Jinyue Chen et al.

Audio-Visual LLM achieves 53.7% accuracy on MSRVTT-QA using modality-augmented training for video understanding.

Fangxun Shu, Lei Zhang, Hao Jiang et al.

ASH uses 2D texture space parameterization of Gaussian splats for real-time high-fidelity animated human rendering.

Haokai Pang, Heming Zhu, Adam Kortylewski et al.