✨Agent S: An Open Agentic Framework that Uses Computers Like a Human

📝 Summary:
Agent S is an open agentic framework enabling autonomous GUI interaction to automate complex tasks. It employs experience-augmented hierarchical planning and an Agent-Computer Interface with MLLMs for enhanced reasoning. Agent S achieves state-of-the-art performance on OSWorld and demonstrates br...

🔹 Publication Date: Published on Oct 10, 2024

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2410.08164
• PDF: https://arxiv.org/pdf/2410.08164
• Github: https://huggingface.co/collections/ranpox/awesome-computer-use-agents

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✨Mamba: Linear-Time Sequence Modeling with Selective State Spaces

📝 Summary:
Mamba, a novel SSM-based model, outperforms Transformers in inference speed and scalability across various modalities by selectively propagating information and using efficient hardware-aware algorith...

🔹 Publication Date: Published on Dec 1, 2023

🔹 Paper Links:
• arXiv Page: https://arxivexplained.com/papers/mamba-linear-time-sequence-modeling-with-selective-state-spaces
• PDF: https://arxiv.org/pdf/2312.00752
• Github: https://github.com/state-spaces/mamba

🔹 Models citing this paper:
• https://huggingface.co/tiiuae/falcon-mamba-7b
• https://huggingface.co/state-spaces/mamba-2.8b-slimpj
• https://huggingface.co/tiiuae/falcon-mamba-7b-instruct

✨ Datasets citing this paper:
• https://huggingface.co/datasets/Sherirto/BD4UI

✨ Spaces citing this paper:
• https://huggingface.co/spaces/openfree/LLM_Quantization
• https://huggingface.co/spaces/FallnAI/Quantize-HF-Models
• https://huggingface.co/spaces/seawolf2357/LLM_Quantization

==================================

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✨AI-Trader: Benchmarking Autonomous Agents in Real-Time Financial Markets

📝 Summary:
AI-Trader evaluates the performance of large language models in real-world financial markets, highlighting their limitations in trading and risk management. AI-generated summary Large Language Models ...

🔹 Publication Date: Published on Dec 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10971
• PDF: https://arxiv.org/pdf/2512.10971
• Project Page: https://ai4trade.ai/
• Github: https://github.com/HKUDS/AI-Trader

==================================

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✨Inferring Compositional 4D Scenes without Ever Seeing One

📝 Summary:
COM4D infers 4D/3D object structure and spatio-temporal configuration from 2D video. It avoids 4D compositional training data by disentangling spatial and temporal attention learning. This purely data-driven method achieves state-of-the-art results in 4D object and composed 3D reconstruction.

🔹 Publication Date: Published on Dec 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.05272
• PDF: https://arxiv.org/pdf/2512.05272
• Project Page: https://berkegokmen1.github.io/com4d/
• Github: https://github.com/insait-institute/COM4D

==================================

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✨FunAudioLLM: Voice Understanding and Generation Foundation Models for Natural Interaction Between Humans and LLMs

📝 Summary:
FunAudioLLM enhances voice interactions by integrating SenseVoice for multilingual speech recognition, emotion detection, and audio event detection with CosyVoice for natural speech generation across ...

🔹 Publication Date: Published on Jul 4, 2024

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2407.04051
• PDF: https://arxiv.org/pdf/2407.04051
• Github: https://github.com/FunAudioLLM

==================================

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✨SmolDocling: An ultra-compact vision-language model for end-to-end multi-modal document conversion

📝 Summary:
SmolDocling is a compact vision-language model that performs end-to-end document conversion with robust performance across various document types using 256M parameters and a new markup format. AI-gene...

🔹 Publication Date: Published on Mar 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2503.11576
• PDF: https://huggingface.co/papers/2502.18443
• Project Page: https://huggingface.co/spaces/docling-project/SmolDocling-256M-Demo
• Github: https://github.com/docling-project/docling

🔹 Models citing this paper:
• https://huggingface.co/docling-project/SmolDocling-256M-preview
• https://huggingface.co/ibm-granite/granite-docling-258M
• https://huggingface.co/docling-project/CodeFormulaV2

✨ Datasets citing this paper:
• https://huggingface.co/datasets/docling-project/SynthCodeNet
• https://huggingface.co/datasets/HuggingFaceM4/DoclingMatix
• https://huggingface.co/datasets/docling-project/SynthChartNet

✨ Spaces citing this paper:
• https://huggingface.co/spaces/ibm-granite/granite-docling-258m-demo
• https://huggingface.co/spaces/ibm-granite/granite-docling-258M-WebGPU
• https://huggingface.co/spaces/docling-project/SmolDocling-256M-Demo

==================================

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✨OpenDevin: An Open Platform for AI Software Developers as Generalist Agents

📝 Summary:
OpenDevin is a platform for developing AI agents that interact with the world by writing code, using command lines, and browsing the web, with support for multiple agents and evaluation benchmarks. AI...

🔹 Publication Date: Published on Jul 23, 2024

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2407.16741
• PDF: https://arxiv.org/pdf/2407.16741
• Github: https://github.com/OpenDevin/OpenDevin/?tab=readme-ov-file#-join-our-community

==================================

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✨Single-stream Policy Optimization

📝 Summary:
Single-stream Policy Optimization (SPO) improves policy-gradient training for Large Language Models by eliminating group-based issues and providing a stable, low-variance learning signal, leading to b...

🔹 Publication Date: Published on Sep 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.13232
• PDF: https://arxiv.org/pdf/2509.13232
• Project Page: https://zhongwenxu.notion.site/Single-stream-Policy-Optimization-26a1c4e140e380d78d51fa4567727f50
• Github: https://github.com/volcengine/verl

🔹 Models citing this paper:
• https://huggingface.co/jingyaogong/MiniMind2-gguf

✨ Datasets citing this paper:
• https://huggingface.co/datasets/dingzihan737/SPO_Qwen3-8B_DAPO_16k_ReTool_Binary

==================================

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✨Qwen2.5-VL Technical Report

📝 Summary:
Qwen2.5-VL, the latest vision-language model, advances visual recognition, document parsing, and video comprehension through dynamic resolution processing, Window Attention, and a native Vision Transf...

🔹 Publication Date: Published on Feb 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2502.13923
• PDF: https://arxiv.org/pdf/2502.13923
• Project Page: https://chat.qwenlm.ai
• Github: https://github.com/QwenLM/Qwen2.5-VL

🔹 Models citing this paper:
• https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct
• https://huggingface.co/Qwen/Qwen2.5-VL-32B-Instruct
• https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct

✨ Datasets citing this paper:
• https://huggingface.co/datasets/xlangai/Jedi
• https://huggingface.co/datasets/IntelligenceLab/VideoHallu
• https://huggingface.co/datasets/turing-motors/MOMIJI

✨ Spaces citing this paper:
• https://huggingface.co/spaces/AntResearchNLP/ViLaBench
• https://huggingface.co/spaces/SmartFlowAI/HuggingFaceMonthlyPaper202502
• https://huggingface.co/spaces/hadadxyz/ai

==================================

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✨WebWalker: Benchmarking LLMs in Web Traversal

📝 Summary:
WebWalkerQA assesses LLMs' ability to traverse websites for high-quality data, showing enhancements when combined with RAG using the WebWalker multi-agent framework. AI-generated summary Retrieval-aug...

🔹 Publication Date: Published on Jan 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2501.07572
• PDF: https://arxiv.org/pdf/2501.07572
• Github: https://alibaba-nlp.github.io/WebWalker/

✨ Datasets citing this paper:
• https://huggingface.co/datasets/callanwu/WebWalkerQA
• https://huggingface.co/datasets/shenxiaofan/WebWalkerQA

✨ Spaces citing this paper:
• https://huggingface.co/spaces/callanwu/WebWalkerQALeaderboard
• https://huggingface.co/spaces/dobval/WebThinker

==================================

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✨Finch: Benchmarking Finance & Accounting across Spreadsheet-Centric Enterprise Workflows

📝 Summary:
Finch, a benchmark for AI agents in enterprise finance and accounting, evaluates performance across complex, real-world workflows using authentic data from Enron and other institutions. AI-generated s...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13168
• PDF: https://arxiv.org/pdf/2512.13168
• Project Page: https://huggingface.co/datasets/FinWorkBench/Finch

✨ Datasets citing this paper:
• https://huggingface.co/datasets/FinWorkBench/Finch

==================================

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✨FIN-bench-v2: A Unified and Robust Benchmark Suite for Evaluating Finnish Large Language Models

📝 Summary:
FIN-bench-v2 is a unified benchmark suite for evaluating Finnish large language models, incorporating diverse datasets and evaluation criteria. AI-generated summary We introduce FIN-bench-v2, a unifie...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.01066
• PDF: https://arxiv.org/pdf/2512.13330
• Github: https://github.com/LumiOpen/lm-evaluation-harness/tree/main/lm_eval/tasks/finbench_v2

==================================

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✨PDFMathTranslate: Scientific Document Translation Preserving Layouts

📝 Summary:
PDFMathTranslate is an open-source software that translates scientific documents while maintaining layout integrity, utilizing advancements in large language models and layout detection. AI-generated ...

🔹 Publication Date: Published on Jul 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2507.03009
• PDF: https://arxiv.org/pdf/2507.03009
• Github: https://github.com/byaidu/pdfmathtranslate

==================================

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✨GlobalBuildingAtlas: An Open Global and Complete Dataset of Building Polygons, Heights and LoD1 3D Models

📝 Summary:
We introduce GlobalBuildingAtlas, a publicly available dataset providing global and complete coverage of building polygons, heights and Level of Detail 1 (LoD1) 3D building models. This is the first o...

🔹 Publication Date: Published on Jun 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2506.04106
• PDF: https://arxiv.org/pdf/2506.04106
• Project Page: https://mediatum.ub.tum.de/1782307
• Github: https://github.com/zhu-xlab/GlobalBuildingAtlas

==================================

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✨GenieDrive: Towards Physics-Aware Driving World Model with 4D Occupancy Guided Video Generation

📝 Summary:
GenieDrive uses a 4D occupancy-based approach with a VAE and Mutual Control Attention for physics-aware driving video generation, improving forecasting accuracy and video quality. AI-generated summary...

🔹 Publication Date: Published on Dec 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12751
• PDF: https://arxiv.org/pdf/2512.12751

==================================

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✨Few-Step Distillation for Text-to-Image Generation: A Practical Guide

📝 Summary:
A systematic study adapts diffusion distillation techniques to text-to-image generation, providing guidelines for successful implementation and deployment. AI-generated summary Diffusion distillation ...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13006
• PDF: https://arxiv.org/pdf/2512.13006
• Github: https://github.com/alibaba-damo-academy/T2I-Distill.git

==================================

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✨CAPTAIN: Semantic Feature Injection for Memorization Mitigation in Text-to-Image Diffusion Models

📝 Summary:
CAPTAIN, a training-free framework, mitigates memorization in diffusion models by modifying latent features during denoising, ensuring prompt fidelity and visual quality. AI-generated summary Diffusio...

🔹 Publication Date: Published on Dec 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10655
• PDF: https://arxiv.org/pdf/2512.10655

==================================

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✨State over Tokens: Characterizing the Role of Reasoning Tokens

📝 Summary:
The State over Tokens (SoT) framework reinterprets reasoning tokens in large language models as computational states rather than linguistic narratives, highlighting the need for a new focus in researc...

🔹 Publication Date: Published on Dec 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12777
• PDF: https://arxiv.org/pdf/2512.12777

==================================

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