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Wei Chen, Zhiyuan Li, Zhen Guo +1 authors
An on-device Planner-Action framework, utilizing Phi-3 Mini for planning and Octopus for execution, employs model fine-tuning and multi-LoRA training to enhance efficiency and multi-domain handling on resource-constrained devices.
Moo Jin Kim, Karl Pertsch, Siddharth Karamcheti +15 authors
OpenVLA, a 7B-parameter open-source vision-language-action model, demonstrates strong performance in generalist manipulation and efficient fine-tuning for new tasks, outperforming larger closed models and from-scratch imitation learning methods.
Xiao Yang, Kai Sun, Hao Xin +24 authors
The Comprehensive RAG Benchmark (CRAG) evaluates RAG solutions with diverse QA tasks, revealing gaps in LLM accuracy and future research directions.
Wilfried Bounsi, Borja Ibarz, Andrew Dudzik +5 authors
A novel TransNAR model combines Transformer-based language understanding with graph neural network solvers to enhance algorithmic reasoning.
Sandeep Mishra, Oindrila Saha, Alan C. Bovik
YouDream generates high-quality, anatomically consistent 3D animals using a text-to-image diffusion model guided by 2D pose priors, showcasing superior creativity and quality compared to prior methods.
Xianhang Li, Haoqin Tu, Mude Hui +9 authors
Enhancing image-text pairs through recaptioning with LLaMA-3 improves model performance in vision-language tasks, including zero-shot retrieval and text-to-image generation.
Xin Lai, Zhuotao Tian, Yukang Chen +3 authors
A novel method called Step-DPO enhances LLMs' mathematical reasoning by optimizing individual reasoning steps, achieving significant accuracy improvements with minimal data and training.
Changyu Chen, Zichen Liu, Chao Du +5 authors
A novel method using the implicit reward model from Direct Preference Optimization (DPO) to iteratively improve the alignment of large language models, achieving superior performance without external feedback.
Linzheng Chai, Shukai Liu, Jian Yang +15 authors
A multilingual code benchmark covering 40 programming languages with 16K test samples is introduced to advance code language model research, along with a multilingual coder model and instruction corpora.
Pengyang Ling, Jiazi Bu, Pan Zhang +6 authors
MotionClone, a training-free framework, uses motion cloning to control text-to-video generation, yielding superior motion fidelity, textual alignment, and temporal consistency.
Namgyu Ho, Sangmin Bae, Taehyeon Kim +6 authors
The Block Transformer architecture enhances inference throughput by applying global-to-local modeling to autoregressive transformers, reducing inference bottlenecks through hierarchical processing and block-level self-attention.
Fei Wang, Wenxuan Zhou, James Y. Huang +4 authors
mDPO, a multimodal preference optimization method, addresses the unconditional preference problem and enhances model performance in multimodal large language models.
Lingyun Zhang, Bin jin, Gaojian Ge +7 authors
A principle for leveraging human priors in data construction is proposed to improve small language models, demonstrating favorable performance on large benchmarks in resource-constrained settings.
Liliang Ren, Yang Liu, Yadong Lu +3 authors
Samba, a hybrid architecture combining State Space Models and Sliding Window Attention, efficiently handles long-range context with lower computational complexity and better memory recall than pure attention or SSM models.
Zhenliang Xue, Yixin Song, Zeyu Mi +3 authors
PowerInfer-2 is a framework that enhances the high-speed inference of large language models on smartphones by utilizing heterogeneous resources and optimizing matrix computations through neuron cluster processing.
Philip Anastassiou, Jiawei Chen, Jitong Chen +43 authors
Seed-TTS is a family of large-scale TTS models that generate high-quality speech with in-context learning, superior controllability, and a non-autoregressive variant using diffusion-based architecture that does not rely on pre-estimated phoneme durations.
Fangfu Liu, Hanyang Wang, Shunyu Yao +3 authors
Physics3D uses a video diffusion model to learn and simulate the physical properties of 3D objects, enabling realistic behavior prediction in virtual environments.
Yang Sui, Yanyu Li, Anil Kag +7 authors
A weight quantization method reduces the size of diffusion-based image generation models while improving generation quality.
Aman Singh Thakur, Kartik Choudhary, Venkat Srinik Ramayapally +2 authors
LLM-as-a-judge method for evaluating LLMs shows promise but varies in performance and alignment with human judges, with smaller models like JudgeLM-7B sometimes outperforming larger ones in ranking tasks.
Shenghai Yuan, Jinfa Huang, Yongqi Xu +7 authors
ChronoMagic-Bench evaluates text-to-video models' ability to generate time-lapse videos with metamorphic amplitude and temporal coherence using novel metrics and a large dataset.
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