✨AgentSwing: Adaptive Parallel Context Management Routing for Long-Horizon Web Agents

📝 Summary:
AgentSwing adaptively manages context for long-horizon web agents using parallel branching and lookahead routing. This state-aware framework outperforms static methods, reducing interactions while improving search efficiency and terminal precision.

🔹 Publication Date: Published on Mar 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.27490
• PDF: https://arxiv.org/pdf/2603.27490

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

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#WebAgents #AI #ContextManagement #ParallelComputing #AgentAI

✨ScheMatiQ: From Research Question to Structured Data through Interactive Schema Discovery

📝 Summary:
ScheMatiQ uses large language models to automatically generate annotation schemas and structured databases from research questions and document collections. Its interactive web interface allows users to steer the extraction, supporting real-world analysis in law and biology.

🔹 Publication Date: Published on Apr 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.09237
• PDF: https://arxiv.org/pdf/2604.09237
• Project Page: https://www.schematiq-ai.com/
• Github: https://github.com/shaharl6000/ScheMatiQ

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

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✨Large Language Models Align with the Human Brain during Creative Thinking

📝 Summary:
Large language models show varying alignment with brain activity during creative thinking tasks, with model size and post-training objectives influencing how well their representations match neural re...

🔹 Publication Date: Published on Apr 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.03480
• PDF: https://arxiv.org/pdf/2604.03480

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨On Semiotic-Grounded Interpretive Evaluation of Generative Art

📝 Summary:
Generative art evaluation framework based on Peircean semiotics assesses symbolic and indexical meaning through hierarchical semiosis graphs, improving alignment with human artistic interpretation. AI...

🔹 Publication Date: Published on Apr 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.08641
• PDF: https://arxiv.org/pdf/2604.08641
• Github: https://github.com/songrise/SemJudge

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Initialisation Determines the Basin: Efficient Codebook Optimisation for Extreme LLM Quantization

📝 Summary:
Additive quantization for LLM compression faces challenges at 2-bit precision due to codebook initialization issues, which OA-EM addresses through output-aware EM initialization based on Hessian-weigh...

🔹 Publication Date: Published on Apr 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.08118
• PDF: https://arxiv.org/pdf/2604.08118
• Github: https://github.com/kenno94-IK/aqlm-oaem

🔹 Models citing this paper:
• https://huggingface.co/kennedyian94/Llama-3.2-3B-AQLM-OA-EM-2Bit-2x8
• https://huggingface.co/kennedyian94/Qwen-2.5-3B-AQLM-OA-EM-2Bit-2x8
• https://huggingface.co/kennedyian94/Llama-3.1-8B-AQLM-OA-EM-2Bit-2x8

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨AVGen-Bench: A Task-Driven Benchmark for Multi-Granular Evaluation of Text-to-Audio-Video Generation

📝 Summary:
AVGen-Bench presents a comprehensive benchmark for text-to-audio-video generation with multi-granular evaluation, revealing gaps between aesthetic quality and semantic accuracy. AI-generated summary T...

🔹 Publication Date: Published on Apr 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.08540
• PDF: https://arxiv.org/pdf/2604.08540
• Project Page: https://microsoft.github.io/AVGen-Bench/
• Github: https://github.com/microsoft/AVGen-Bench

✨ Datasets citing this paper:
• https://huggingface.co/datasets/microsoft/AVGen-Bench

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Backdoor Attacks on Decentralised Post-Training

📝 Summary:
This paper introduces the first backdoor attack on pipeline parallelism in decentralized LLM post-training. An adversary controlling an intermediate stage can significantly misalign the model, reducing alignment from 80% to 6% with a trigger word, even resisting safety training.

🔹 Publication Date: Published on Mar 31

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.02372
• PDF: https://arxiv.org/pdf/2604.02372

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

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#BackdoorAttack #LLM #DecentralizedAI #AISecurity #MachineLearning

✨Multi-User Large Language Model Agents

📝 Summary:
Multi-user LLM agents struggle with conflicting objectives, privacy, and coordination. This study formalizes the problem and reveals systematic gaps in current LLMs. They fail to prioritize instructions, violate privacy, and suffer coordination bottlenecks.

🔹 Publication Date: Published on Mar 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.08567
• PDF: https://arxiv.org/pdf/2604.08567
• Project Page: https://korde-ai.github.io/Multi-User-LLM-Agent/
• Github: https://github.com/Korde-AI/Multi-User-LLM-Agent

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

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✨p1: Better Prompt Optimization with Fewer Prompts

📝 Summary:
Research reveals that prompt optimization effectiveness depends on the balance between response stochasticity and system prompt quality variance, leading to the development of a filtering method that ...

🔹 Publication Date: Published on Apr 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.08801
• PDF: https://arxiv.org/pdf/2604.08801

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

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✨EquiformerV3: Scaling Efficient, Expressive, and General SE(3)-Equivariant Graph Attention Transformers

📝 Summary:
EquiformerV3 advances SE(3)-equivariant graph neural networks through enhanced efficiency, expressivity, and generality via optimized implementation, improved architectural components, and novel activ...

🔹 Publication Date: Published on Apr 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.09130
• PDF: https://arxiv.org/pdf/2604.09130
• Github: https://github.com/atomicarchitects/equiformer_v3

🔹 Models citing this paper:
• https://huggingface.co/yilunliao/equiformer_v3
• https://huggingface.co/mirror-physics/equiformer_v3

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Semantic Richness or Geometric Reasoning? The Fragility of VLM's Visual Invariance

📝 Summary:
Vision-Language Models show significant vulnerabilities under geometric transformations, lacking robust spatial invariance and equivariance despite strong semantic capabilities. AI-generated summary T...

🔹 Publication Date: Published on Apr 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.01848
• PDF: https://arxiv.org/pdf/2604.01848
• Project Page: https://xthomasbu.github.io/visual_invariance/

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

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✨Cross-Modal Emotion Transfer for Emotion Editing in Talking Face Video

📝 Summary:
A novel cross-modal emotion transfer approach generates expressive talking face videos by modeling emotion semantic vectors between speech and visual feature spaces, achieving superior emotion accurac...

🔹 Publication Date: Published on Apr 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.07786
• PDF: https://arxiv.org/pdf/2604.07786
• Project Page: https://chanhyeok-choi.github.io/C-MET/
• Github: https://github.com/ChanHyeok-Choi/C-MET

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

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✨Envisioning the Future, One Step at a Time

📝 Summary:
Autoregressive diffusion models predict open-set future scene dynamics by modeling sparse point trajectories, enabling fast and scalable multi-modal motion prediction with physical plausibility. AI-ge...

🔹 Publication Date: Published on Apr 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.09527
• PDF: https://arxiv.org/pdf/2604.09527
• Project Page: https://compvis.github.io/myriad
• Github: https://github.com/compvis/myriad

🔹 Models citing this paper:
• https://huggingface.co/CompVis/myriad

✨ Datasets citing this paper:
• https://huggingface.co/datasets/CompVis/owm-95
• https://huggingface.co/datasets/CompVis/myriad-physics

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Process Reward Agents for Steering Knowledge-Intensive Reasoning

📝 Summary:
Process Reward Agents provide domain-grounded, online step-wise rewards for frozen policies in knowledge-intensive reasoning, enabling improved search-based decoding and generalizing across different ...

🔹 Publication Date: Published on Apr 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.09482
• PDF: https://arxiv.org/pdf/2604.09482
• Project Page: https://process-reward-agents.github.io/

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

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✨Robust Reasoning Benchmark

📝 Summary:
Research reveals that large language models exhibit fragile reasoning capabilities when subjected to perturbations, with open-weight models showing significant accuracy drops and evidence of memory po...

🔹 Publication Date: Published on Mar 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.08571
• PDF: https://arxiv.org/pdf/2604.08571

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

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✨Cactus: Accelerating Auto-Regressive Decoding with Constrained Acceptance Speculative Sampling

📝 Summary:
Speculative sampling methods are enhanced by formulating them as constrained optimization problems, enabling controlled distribution divergence while maintaining high acceptance rates and output quali...

🔹 Publication Date: Published on Apr 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.04987
• PDF: https://arxiv.org/pdf/2604.04987
• Github: https://github.com/MANGA-UOFA/Cactus

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

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✨MixFlow: Mixed Source Distributions Improve Rectified Flows

📝 Summary:
Rectified flows and diffusion models are improved through κ-FC formulation that conditions the source distribution and MixFlow training strategy that reduces generative path curvatures and enhances sa...

🔹 Publication Date: Published on Apr 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.09181
• PDF: https://arxiv.org/pdf/2604.09181
• Github: https://github.com/NazirNayal8/MixFlow

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

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#RectifiedFlows #DiffusionModels #GenerativeAI #MachineLearning #AIResearch

✨Beyond the Assistant Turn: User Turn Generation as a Probe of Interaction Awareness in Language Models

📝 Summary:
User-turn generation probes LLM interaction awareness, decoupled from task accuracy. This awareness is often latent but revealed by higher temperature sampling and can be improved through post-training, uncovering a new dimension of LLM behavior.

🔹 Publication Date: Published on Apr 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.02315
• PDF: https://arxiv.org/pdf/2604.02315

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

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#LLM #NLP #AI #InteractionAwareness #UserTurnGeneration

✨Pseudo-Unification: Entropy Probing Reveals Divergent Information Patterns in Unified Multimodal Models

📝 Summary:
Unified multimodal models suffer from pseudo-unification due to asymmetric encoding and split response patterns, requiring consistent information flow for genuine multimodal synergy. AI-generated summ...

🔹 Publication Date: Published on Apr 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.10949
• PDF: https://arxiv.org/pdf/2604.10949

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

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✨CodeTracer: Towards Traceable Agent States

📝 Summary:
CodeTracer is a tracing architecture that analyzes code agent execution by reconstructing state transitions and localizing failures in complex multi-stage workflows. AI-generated summary Code agents a...

🔹 Publication Date: Published on Apr 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.11641
• PDF: https://arxiv.org/pdf/2604.11641

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

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✨OmniShow: Unifying Multimodal Conditions for Human-Object Interaction Video Generation

📝 Summary:
OmniShow is an end-to-end framework for human-object interaction video generation using multimodal conditions like text, images, audio, and pose. It uses unified conditioning, gated attention, and decoupled training to achieve state-of-the-art performance despite data scarcity. A new benchmark, H...

🔹 Publication Date: Published on Apr 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/pdf/2604.11804
• PDF: https://arxiv.org/pdf/2604.11804
• Project Page: https://correr-zhou.github.io/OmniShow
• Github: https://github.com/Correr-Zhou/OmniShow

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

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#AI #DataScience #MachineLearning #HuggingFace #Research