ML Research Hub
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Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.

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CityRAG: Stepping Into a City via Spatially-Grounded Video Generation

📝 Summary:
CityRAG generates long-term, physically grounded video sequences that maintain environmental consistency and support complex navigation through real-world geography using geo-registered data as contex...

🔹 Publication Date: Published on Apr 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19741
• PDF: https://arxiv.org/pdf/2604.19741
• Project Page: https://cityrag.github.io/

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#VideoGeneration #GenerativeAI #SpatialAI #ComputerVision #UrbanSimulation
RDP LoRA: Geometry-Driven Identification for Parameter-Efficient Adaptation in Large Language Models

📝 Summary:
Using geometric trajectory analysis with the Ramer-Douglas-Peucker algorithm to select optimal layers for parameter-efficient fine-tuning of large language models, achieving better performance than fu...

🔹 Publication Date: Published on Apr 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19321
• PDF: https://arxiv.org/pdf/2604.19321

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#AI #DataScience #MachineLearning #HuggingFace #Research
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Cortex 2.0: Grounding World Models in Real-World Industrial Deployment

📝 Summary:
Cortex 2.0 introduces a plan-and-act control system for reliable long-horizon robotic manipulation. It generates and evaluates future trajectories in visual latent space, outperforming reactive Vision-Language-Action models. This demonstrates world-model-based planning's reliability in complex in...

🔹 Publication Date: Published on Apr 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.20246
• PDF: https://arxiv.org/pdf/2604.20246

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#AI #DataScience #MachineLearning #HuggingFace #Research
SWE-chat: Coding Agent Interactions From Real Users in the Wild

📝 Summary:
SWE-chat presents a large-scale dataset of real coding agent interactions that reveals significant inefficiencies and challenges in current AI-assisted development practices. AI-generated summary A I ...

🔹 Publication Date: Published on Apr 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.20779
• PDF: https://arxiv.org/pdf/2604.20779

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#AI #DataScience #MachineLearning #HuggingFace #Research
LLaDA2.0-Uni: Unifying Multimodal Understanding and Generation with Diffusion Large Language Model

📝 Summary:
LLaDA2.0-Uni is a unified discrete diffusion language model that integrates multimodal understanding and generation through a semantic discrete tokenizer, MoE-based backbone, and diffusion decoder, ac...

🔹 Publication Date: Published on Apr 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.20796
• PDF: https://arxiv.org/pdf/2604.20796
• Github: https://github.com/inclusionAI/LLaDA2.0-Uni

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#AI #DataScience #MachineLearning #HuggingFace #Research
DR-Venus: Towards Frontier Edge-Scale Deep Research Agents with Only 10K Open Data

📝 Summary:
DR-Venus-4B is a 4-billion-parameter deep research agent trained entirely on open data using agentic supervised fine-tuning and reinforcement learning with turn-level rewards to achieve superior perfo...

🔹 Publication Date: Published on Apr 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19859
• PDF: https://arxiv.org/pdf/2604.19859
• Project Page: https://huggingface.co/collections/inclusionAI/dr-venus
• Github: https://github.com/inclusionAI/DR-Venus/tree/master/Inference

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#AI #DataScience #MachineLearning #HuggingFace #Research
WavAlign: Enhancing Intelligence and Expressiveness in Spoken Dialogue Models via Adaptive Hybrid Post-Training

📝 Summary:
Spoken dialogue models face challenges in expressiveness despite end-to-end approaches, but a modality-aware adaptive post-training method using constrained preference updates and explicit anchoring i...

🔹 Publication Date: Published on Apr 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.14932
• PDF: https://arxiv.org/pdf/2604.14932

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#AI #DataScience #MachineLearning #HuggingFace #Research
MMCORE: MultiModal COnnection with Representation Aligned Latent Embeddings

📝 Summary:
MMCORE is a unified framework for multimodal image generation and editing that uses a pre-trained Vision-Language Model to predict semantic visual embeddings for diffusion model conditioning, enabling...

🔹 Publication Date: Published on Apr 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19902
• PDF: https://arxiv.org/pdf/2604.19902

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CreativeGame:Toward Mechanic-Aware Creative Game Generation

📝 Summary:
A multi-agent system for iterative HTML5 game generation that uses programmatic rewards, lineage memory, runtime validation, and mechanic-guided planning to enable interpretable version-to-version evo...

🔹 Publication Date: Published on Apr 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19926
• PDF: https://arxiv.org/pdf/2604.19926

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Self-Evolving LLM Memory Extraction Across Heterogeneous Tasks

📝 Summary:
LLM-based assistants require heterogeneous memory extraction capabilities, which are evaluated through the BEHEMOTH benchmark, with CluE offering improved performance through cluster-based prompt opti...

🔹 Publication Date: Published on Apr 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.11610
• PDF: https://arxiv.org/pdf/2604.11610
• Github: https://github.com/ayyyq/heterogeneous-memory-extraction

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Exploring Spatial Intelligence from a Generative Perspective

📝 Summary:
Generative spatial intelligence benchmark evaluates and enhances 3D spatial constraint manipulation in image generation through real-world and synthetic datasets. AI-generated summary Spatial intellig...

🔹 Publication Date: Published on Apr 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.20570
• PDF: https://arxiv.org/pdf/2604.20570
• Project Page: https://aim-uofa.github.io/GSI-Bench/
• Github: https://github.com/aim-uofa/GSI-Bench

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Convergent Evolution: How Different Language Models Learn Similar Number Representations

📝 Summary:
Transformers and other language models exhibit periodic numerical representations in their Fourier domains, with some models developing geometrically separable features for linear classification of nu...

🔹 Publication Date: Published on Apr 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.20817
• PDF: https://arxiv.org/pdf/2604.20817
• Project Page: https://convergent-evolution.github.io/

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#AI #DataScience #MachineLearning #HuggingFace #Research
Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges

📝 Summary:
Reward hacking in aligned language models stems from optimizing expressive policies against compressed reward signals, leading to systematic misalignment behaviors that generalize beyond initial short...

🔹 Publication Date: Published on Apr 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13602
• PDF: https://arxiv.org/pdf/2604.13602
• Project Page: https://github.com/xhwang22/Awesome-Reward-Hacking
• Github: https://github.com/xhwang22/Awesome-Reward-Hacking

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Near-Future Policy Optimization

📝 Summary:
Mixed-policy reinforcement learning approach using near-future policy optimization to accelerate convergence and improve performance by balancing trajectory quality and variance. AI-generated summary ...

🔹 Publication Date: Published on Apr 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.20733
• PDF: https://arxiv.org/pdf/2604.20733

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Scaling Test-Time Compute for Agentic Coding

📝 Summary:
This framework improves long-horizon agentic coding by using compact trajectory representations for test-time scaling. It employs Recursive Tournament Voting and adapted Parallel-Distill-Refine to significantly boost coding agent performance on benchmarks.

🔹 Publication Date: Published on Apr 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.16529
• PDF: https://arxiv.org/pdf/2604.16529

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#AgenticAI #CodingAgents #MachineLearning #AIResearch #DeepLearning
1
ReImagine: Rethinking Controllable High-Quality Human Video Generation via Image-First Synthesis

📝 Summary:
A pose- and viewpoint-controllable human video generation method combines image generation with SMPL-X motion guidance and video diffusion models to produce high-quality, temporally consistent videos....

🔹 Publication Date: Published on Apr 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19720
• PDF: https://arxiv.org/pdf/2604.19720
• Project Page: https://keruzheng.github.io/ReImagine-Project/
• Github: https://github.com/Taited/ReImagine

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AI scientists produce results without reasoning scientifically

📝 Summary:
Large language model-based scientific agents demonstrate consistent reasoning patterns that lack key epistemic features of scientific inquiry, regardless of task type or successful context, indicating...

🔹 Publication Date: Published on Apr 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.18805
• PDF: https://arxiv.org/pdf/2604.18805
• Project Page: https://lamalab-org.github.io/corral/

Datasets citing this paper:
https://huggingface.co/datasets/jablonkagroup/corral-traces
https://huggingface.co/datasets/jablonkagroup/corral-oss-trace-logprobs
https://huggingface.co/datasets/jablonkagroup/corral_runs_reports

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Diverse Dictionary Learning

📝 Summary:
Without strong assumptions, latent variable recovery is made possible through diverse dictionary learning that identifies set-theoretic relationships and structures from observational data. AI-generat...

🔹 Publication Date: Published on Apr 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.17568
• PDF: https://arxiv.org/pdf/2604.17568

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Tadabur: A Large-Scale Quran Audio Dataset

📝 Summary:
D e s p i t e g r o w i n g i n t e r e s t i n Q u r a n i c d a t a r e s e a r c h , e x i s t i n g Q u r a n d a t a s e t s r e m a i n l i m i t e d i n b o t h s c a l e a n d d i v e r s i t ...

🔹 Publication Date: Published on Apr 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.18932
• PDF: https://arxiv.org/pdf/2604.18932
• Project Page: https://fherran.github.io/tadabur/
• Github: https://github.com/fherran/tadabur

Datasets citing this paper:
https://huggingface.co/datasets/FaisaI/tadabur

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SAVOIR: Learning Social Savoir-Faire via Shapley-based Reward Attribution

📝 Summary:
SAVOIR framework uses cooperative game theory to improve social intelligence in language agents by combining expected utility shifts and Shapley values for better credit assignment in dialogue systems...

🔹 Publication Date: Published on Apr 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.18982
• PDF: https://arxiv.org/pdf/2604.18982
• Github: https://github.com/jyyyyy0/SAVOIR

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Visual Reasoning through Tool-supervised Reinforcement Learning

📝 Summary:
A novel Tool-supervised Reinforcement Learning framework is presented that enables multimodal large language models to effectively learn tool-use for complex visual reasoning through a two-stage curri...

🔹 Publication Date: Published on Apr 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19945
• PDF: https://arxiv.org/pdf/2604.19945

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

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#AI #DataScience #MachineLearning #HuggingFace #Research