Neural intel Pod

This research addresses the challenge of  catastrophic forgetting  in large language models during  continual learning , where adapting to new tasks degrades performance on old ones. To overcome this, the authors introduce a novel approach that utilizes  adaptive singular value decomposition (SVD)  to identify and preserve important knowledge while allowing flexible learning of new information. Th...

Meta AI has introduced its Llama 4 family of large language models , highlighting two new open-weight models:  Llama 4 Scout and Llama 4 Maverick , along with a powerful, still-training model called  Llama 4 Behemoth .  These multimodal models feature innovations like Mixture-of-Experts architecture and significantly expanded context windows , outperforming previous Llama iterations and competing...

This paper introduces  UniOcc , a new benchmark for  3D occupancy forecasting and prediction  in autonomous driving. It  unifies data  from real-world datasets like nuScenes and Waymo with synthetic data from CARLA and OpenCOOD, providing  2D/3D occupancy labels and voxel-level flow . UniOcc also offers  novel evaluation metrics  that don't rely solely on imperfect ground truth and includes a ...

This research introduces a novel method for generating counterfactual explanations for graph-based predictions. The approach utilizes a permutation equivariant graph variational autoencoder (PEGVAE) to create a meaningful latent space representation of graphs.  By traversing this latent space guided by the classifier, the method identifies minimally altered graphs with a different classification....

The provided research paper explores the novel problem of  continual forgetting  in pre-trained vision models, where the goal is to  sequentially remove specific unwanted knowledge  while retaining the model's performance on other tasks. To address this, the authors introduce  Group Sparse LoRA (GS-LoRA++) , a parameter-efficient fine-tuning approach that uses  low-rank adaptation  with a  gro...

The provided research explores optimizing communication and sensing for autonomous vehicles using millimeter wave technology and orthogonal frequency-division multiplexing.  Facing dynamic environments and the impact of wireless conditions on mmWave, the authors propose an adaptive system.  This system employs reinforcement learning, considering queue state and channel state information.  The goal...

Recent progress in video generation still struggles with issues like motion instability and prompt alignment. To address this, the study explores incorporating human preferences into advanced flow-based video generation models. The authors introduce a large, new dataset of human-annotated video preferences across visual quality, motion quality, and text alignment. They also develop a multi-dimensi...

This research paper introduces  AnimeGamer , a novel method for creating  infinite anime life simulation games . Unlike previous work limited to static images or finite gameplay, AnimeGamer uses a  multimodal large language model  to process user instructions and predict subsequent game states. These states include  dynamic animation shots and updated character attributes , aiming for a more immer...

The provided research introduces NoProp, a novel method for training neural networks that deviates from traditional backpropagation by eliminating both forward and backward passes. Instead, it draws inspiration from diffusion models, where each layer learns independently to denoise a noisy version of the target. This approach trains networks without hierarchical representation learning in the conv...

The provided paper introduces  ACPBench Hard , a new benchmark designed to evaluate the reasoning capabilities of large language models for automated planning. This benchmark extends the original ACPBench by featuring  open-ended, generative versions of planning-related questions  across various tasks, mirroring the challenges faced by symbolic planners. The authors tested several large language a...

From Amazon's blog

Dynamic 4D Modeling from Casual Video

The provided research paper introduces KDTalker, a novel method for generating realistic audio-driven talking portraits by combining implicit 3D keypoints with a spatiotemporal diffusion model. This framework addresses limitations in existing techniques by achieving high lip synchronization accuracy and diverse head poses while maintaining computational efficiency. KDTalker leverages unsupervised...

AI2 has announced OLMo 2 , a new family of fully open 7B and 13B language models demonstrating  performance on par with or exceeding similarly sized open models , even rivaling open-weight models like Llama 3.1. This release includes not only model weights but also  data, code, and evaluation frameworks , emphasizing truly open science. Key advancements in OLMo 2 involve  improved training stabili...

Stable 3D Shape Correspondence via Registration

The provided text introduces  ProjectEval , a new benchmark for automatically evaluating the project-level code generation capabilities of programming agents by simulating user interactions.  ProjectEval  aims to address the limitations of existing benchmarks, such as a lack of automated user-centric evaluation and result explainability. The benchmark includes diverse real-world tasks with varying...

This research introduces a novel framework using  elicitation and execution policies  to improve how  embodied AI agents  express their confidence in complex, open-ended environments like Minecraft. The authors demonstrate that  structured reasoning techniques , such as Chain-of-Thought and Plan & Solve, significantly enhance an agent's ability to  calibrate its confidence and predict fail...

The provided research introduces  VLM-Attention , a novel StarCraft II environment designed to better reflect human perception and decision-making by incorporating RGB visuals and natural language. This framework utilizes vision-language models with specialized mechanisms for unit targeting, knowledge retrieval for tactical decisions, and dynamic role assignment for coordinated multi-agent behavio...

The provided research paper introduces a novel attack method,  M-Attack , designed to effectively fool sophisticated commercial large vision-language models like GPT-4.5 and Gemini. The paper highlights the  limitations of existing attack strategies  which often produce uniform and semantically vague perturbations, failing against these robust models.  M-Attack overcomes these issues  by focusing...

This paper introduces a  deep learning-based method  for the  generalized inverse design  of complex  multi-port radio-frequency and sub-terahertz electromagnetic structures  and integrated circuits. This innovative approach uses  deep neural networks  to accurately predict the properties of arbitrary-shaped designs, significantly  speeding up the synthesis process  compared to traditional methods...

Cool twitter find

R1 with vision?

The provided files detail  OWL , an innovative framework built upon CAMEL-AI, designed for  multi-agent collaboration  to automate real-world tasks. The README.md offers a comprehensive overview of OWL's  features , including toolkits for web interaction, document processing, and code execution, along with  installation instructions  using various methods like uv, venv, conda, and Docker. The ...

That

Unsloth's documentation provides a comprehensive guide to fine-tuning large language models , particularly for beginners.  It outlines the benefits of fine-tuning , such as improved domain knowledge and task-specific optimization, and compares it to methods like RAG.  The guide details essential steps , including choosing the right model and fine-tuning method like LoRA or QLoRA, preparing dat...