✨Preferences of a Voice-First Nation: Large-Scale Pairwise Evaluation and Preference Analysis for TTS in Indian Languages

📝 Summary:
A controlled multidimensional pairwise evaluation framework for multilingual TTS systems was developed using linguistic control and perceptual annotations across 10 Indic languages. AI-generated summa...

🔹 Publication Date: Published on Apr 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.21481
• PDF: https://arxiv.org/pdf/2604.21481

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Seeing Isn't Believing: Uncovering Blind Spots in Evaluator Vision-Language Models

📝 Summary:
Current vision-language models used for evaluating image-to-text and text-to-image tasks show significant reliability issues in detecting various types of output errors, particularly fine-grained comp...

🔹 Publication Date: Published on Apr 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.21523
• PDF: https://arxiv.org/pdf/2604.21523
• Github: https://github.com/AI4Bharat/focus

✨ Datasets citing this paper:
• https://huggingface.co/datasets/ai4bharat/Focus

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨AutoResearchBench: Benchmarking AI Agents on Complex Scientific Literature Discovery

📝 Summary:
AutoResearchBench is a new benchmark evaluating AI agents on complex scientific literature discovery tasks. It features deep and wide research, demanding in-depth comprehension and fine-grained information use. Even powerful LLMs show very low accuracy, highlighting the significant challenge for ...

🔹 Publication Date: Published on Apr 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.25256
• PDF: https://arxiv.org/pdf/2604.25256
• Project Page: https://cheryou.github.io/autoresearchbench.github.io/
• Github: https://github.com/CherYou/AutoResearchBench

✨ Datasets citing this paper:
• https://huggingface.co/datasets/Lk123/AutoResearchBench

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

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#AI #LLMs #Benchmarking #ScientificResearch #AIAgents

✨MAIC-UI: Making Interactive Courseware with Generative UI

📝 Summary:
MAIC-UI is a zero-code system for educators to rapidly create and edit interactive STEM courseware using structured knowledge analysis and incremental generation. It significantly improves editing efficiency, student learnability, and STEM learning outcomes.

🔹 Publication Date: Published on Apr 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.25806
• PDF: https://arxiv.org/pdf/2604.25806
• Project Page: https://open.maic.chat/
• Github: https://github.com/THU-MAIC/MAIC-UI

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

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#EdTech #GenerativeAI #STEMEducation #NoCode #Courseware

✨Step-Audio-R1.5 Technical Report

📝 Summary:
Audio language models trained with reinforcement learning from verified rewards suffer from reduced conversational quality, prompting a shift toward reinforcement learning from human feedback for impr...

🔹 Publication Date: Published on Apr 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.25719
• PDF: https://arxiv.org/pdf/2604.25719

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

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✨Offline Evaluation Measures of Fairness in Recommender Systems

📝 Summary:
This research identifies and addresses limitations in current recommender system fairness evaluation measures. It provides theoretical analysis, develops novel approaches, and offers guidelines for selecting appropriate measures to improve fairness assessment.

🔹 Publication Date: Published on Apr 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.25032
• PDF: https://arxiv.org/pdf/2604.25032
• Project Page: https://algorithms.dk/fairness-in-recommender-systems/

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨V-GRPO: Online Reinforcement Learning for Denoising Generative Models Is Easier than You Think

📝 Summary:
Researchers developed a novel method called Variational GRPO that improves text-to-image synthesis by combining ELBO-based surrogates with Group Relative Policy Optimization, achieving faster and more...

🔹 Publication Date: Published on Apr 25

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.23380
• PDF: https://arxiv.org/pdf/2604.23380
• Github: https://github.com/tang-bd/v-grpo

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨The Last Harness You'll Ever Build

📝 Summary:
This paper introduces a two-level framework to automate AI agent harness engineering. It uses evolutionary loops to optimize task-specific harnesses and a meta-evolutionary loop to automate the optimization process itself, eliminating the need for manual design. This enables rapid agent adaptatio...

🔹 Publication Date: Published on Apr 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.21003
• PDF: https://arxiv.org/pdf/2604.21003

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

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✨Turning the TIDE: Cross-Architecture Distillation for Diffusion Large Language Models

📝 Summary:
TIDE is a framework for cross-architecture distillation of diffusion LLMs. It uses specialized modules to enable knowledge transfer between different architectures and tokenizers, significantly improving performance for smaller student models, especially in code generation.

🔹 Publication Date: Published on Apr 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.26951
• PDF: https://arxiv.org/pdf/2604.26951
• Project Page: https://pku-yuangroup.github.io/TIDE-Page/
• Github: https://pku-yuangroup.github.io/TIDE-Page/

🔹 Models citing this paper:
• https://huggingface.co/TIDE-dllm/distill-WeDLM-TIDE_Shared
• https://huggingface.co/TIDE-dllm/distill-LLaDA2-TIDE_Cross
• https://huggingface.co/TIDE-dllm/distill-LLaDA2-TIDE_Shared

✨ Datasets citing this paper:
• https://huggingface.co/datasets/TIDE-dllm/distill_llada2_sft
• https://huggingface.co/datasets/TIDE-dllm/distill_wedlm_sft

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

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✨Accelerating RL Post-Training Rollouts via System-Integrated Speculative Decoding

📝 Summary:
Speculative decoding accelerates RL post-training by preserving output distributions while improving rollout throughput, with projected 2.5x speedup at large scales. AI-generated summary RL post-train...

🔹 Publication Date: Published on Apr 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.26779
• PDF: https://arxiv.org/pdf/2604.26779

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

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✨ClawGym: A Scalable Framework for Building Effective Claw Agents

📝 Summary:
ClawGym presents a scalable framework for developing Claw-style personal agents with synthetic training data, verified workspaces, and benchmark evaluation. AI-generated summary Claw-style environment...

🔹 Publication Date: Published on Apr 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.26904
• PDF: https://arxiv.org/pdf/2604.26904
• Project Page: https://github.com/ClawGym

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

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✨Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising

📝 Summary:
X-WAM is a unified 4D world model that combines real-time robotic action execution with high-fidelity 4D world synthesis using pretrained video diffusion models and asynchronous noise sampling for imp...

🔹 Publication Date: Published on Apr 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.26694
• PDF: https://arxiv.org/pdf/2604.26694
• Project Page: https://sharinka0715.github.io/X-WAM/

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents

📝 Summary:
GLM-5V-Turbo is a foundation model that integrates multimodal perception as a core reasoning component for AI agents. This improves performance in multimodal coding and visual tool use, while maintaining strong text-only capabilities.

🔹 Publication Date: Published on Apr 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.26752
• PDF: https://arxiv.org/pdf/2604.26752
• Github: https://github.com/zai-org/GLM-V

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

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✨Diffusion Templates: A Unified Plugin Framework for Controllable Diffusion

📝 Summary:
Diffusion Templates presents a unified framework that decouples base-model inference from controllable capabilities, enabling modular and composable control methods across various diffusion model appl...

🔹 Publication Date: Published on Apr 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.24351
• PDF: https://arxiv.org/pdf/2604.24351
• Project Page: https://modelscope.github.io/diffusion-templates-web/

🔹 Models citing this paper:
• https://huggingface.co/DiffSynth-Studio/Template-KleinBase4B-ControlNet
• https://huggingface.co/DiffSynth-Studio/Template-KleinBase4B-Brightness
• https://huggingface.co/DiffSynth-Studio/Template-KleinBase4B-SoftRGB

✨ Datasets citing this paper:
• https://huggingface.co/datasets/DiffSynth-Studio/ImagePulseV2-Edit-Inpaint
• https://huggingface.co/datasets/DiffSynth-Studio/ImagePulseV2-Edit-Background
• https://huggingface.co/datasets/DiffSynth-Studio/ImagePulseV2-Edit-Change

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

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✨FASH-iCNN: Making Editorial Fashion Identity Inspectable Through Multimodal CNN Probing

📝 Summary:
FASH-iCNN is a multimodal system that identifies fashion house, era, and color tradition from garment photographs with high accuracy, revealing that texture and luminance are primary carriers of edito...

🔹 Publication Date: Published on Apr 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.26186
• PDF: https://arxiv.org/pdf/2604.26186

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

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✨A Survey on LLM-based Conversational User Simulation

📝 Summary:
This paper surveys recent advancements in LLM-based conversational user simulation. It introduces a novel taxonomy of user granularity and simulation objectives, analyzing core techniques and evaluation methodologies to inform future research.

🔹 Publication Date: Published on Apr 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.24977
• PDF: https://arxiv.org/pdf/2604.24977

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

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✨Tequila: Trapping-free Ternary Quantization for Large Language Models

📝 Summary:
Tequila is a new ternary quantization method for LLMs that solves deadzone trapping. It reactivates trapped weights as dynamic biases, significantly improving accuracy and inference speed. This makes LLM deployment on resource-constrained devices practical.

🔹 Publication Date: Published on Sep 28, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.23809
• PDF: https://arxiv.org/pdf/2509.23809
• Github: https://github.com/Tencent/AngelSlim

🔹 Models citing this paper:
• https://huggingface.co/AngelSlim/Qwen3-a3B_eagle3
• https://huggingface.co/AngelSlim/Qwen3-32B_eagle3
• https://huggingface.co/AngelSlim/Qwen3-1.7B_eagle3

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

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✨Large Language Models Explore by Latent Distilling

📝 Summary:
Exploratory Sampling ESamp boosts LLM diversity beyond lexical variation. It uses a lightweight Distiller to predict hidden representations, biasing decoding towards novel semantic patterns via prediction error. ESamp boosts reasoning efficiency and creative writing, with low overhead.

🔹 Publication Date: Published on Apr 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.24927
• PDF: https://arxiv.org/pdf/2604.24927
• Github: https://github.com/LinesHogan/tllm

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

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#LLM #AI #NLP #DeepLearning #GenerativeAI

✨Probing Visual Planning in Image Editing Models

📝 Summary:
This paper redefines visual planning as a single-step image transformation using abstract puzzles for evaluation. Their EAR paradigm and AMAZE dataset reveal that current AI models, despite finetuning, cannot match human zero-shot efficiency, highlighting a gap in visual reasoning.

🔹 Publication Date: Published on Apr 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.22868
• PDF: https://arxiv.org/pdf/2604.22868
• Project Page: https://spatigen.github.io/amaze.io/
• Github: https://github.com/spatigen/amaze

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

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#VisualPlanning #ImageEditing #ComputerVision #AIResearch #MachineLearning