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Kevin Qinghong Lin, Batu EI, Yuhong Shi +3 authors
A multi-agent framework automates data journalism by generating evidence-grounded, multimodal news stories while maintaining transparency and verifiability.
Jingdi Lei, Di Zhang, Junxian Li +7 authors
A lightweight memory mechanism called δ-mem enhances large language models by augmenting a frozen attention backbone with a compact associative memory state that provides low-rank corrections to attention computations.
Jiajie Jin, Yuyang Hu, Kai Qiu +15 authors
An AI framework called Arbor enables autonomous scientific research by combining strategic coordination, isolated hypothesis testing, and a persistent knowledge tree to iteratively improve research outcomes across multiple domains.
Wei Zhou, Xuanhe Zhou, Shaokun Han +5 authors
Large language model agents' memory systems have evolved into complex data management frameworks requiring systematic evaluation across multiple modules and workloads to understand their performance characteristics and trade-offs.
Hongyi Liu, Haoyan Yang, Tao Jiang +3 authors
SkillsVote is a governance framework for long-horizon LLM agents that manages reusable skills through structured collection, recommendation, and evolution processes.
Bin Wu, Mengqi Huang, Shaojin Wu +4 authors
Stream-R1 improves video diffusion model distillation by adaptively weighting supervision based on reliability and perplexity, enhancing visual quality, motion quality, and text alignment without additional computational overhead.
Yibo Wang, Lei Wang, Yue Deng +7 authors
DeepResearchEval presents an automated framework for creating complex research tasks and evaluating them through agent-based methods that adapt to task specifics and verify facts without relying on citations.
Team HY-World, Chenjie Cao, Xuhui Zuo +42 authors
HY-World 2.0 is a multi-modal world model framework that generates high-fidelity 3D Gaussian Splatting scenes from diverse inputs using specialized modules for panorama generation, trajectory planning, world expansion, and composition, along with an enhanced rendering platform for interactive 3D exploration.
Ali Slim, Haydar Hamieh, Jawad Kotaich +5 authors
QuanBench+ evaluates large language models on quantum code generation across multiple frameworks using functional testing and repair-based feedback, revealing significant progress but persistent dependence on framework-specific knowledge.
Dongyoung Kim, Huiwon Jang, Myungkyu Koo +65 authors
RLDX-1 is a general-purpose robotic policy for dexterous manipulation that integrates heterogeneous modalities through a Multi-Stream Action Transformer architecture, demonstrating superior performance in complex real-world tasks compared to existing vision-language-action models.
Zhuofeng Li, Haoxiang Zhang, Cong Wei +16 authors
Direct corpus interaction enables more effective agentic search by allowing agents to query raw text directly, outperforming traditional retrieval methods in complex tasks.
Ji Zeng, Dayuan Fu, Tiantian Mi +14 authors
Agentic mid-training enables large language models to develop autonomous software engineering capabilities through specialized data synthesis techniques that bridge the gap between static training data and dynamic development environments.
Dongrui Liu, Qihan Ren, Chen Qian +40 authors
AI agents face safety and security challenges from autonomous tool use and environmental interactions, requiring advanced guardrail frameworks for risk diagnosis and transparent monitoring.
Mahtab Bigverdi, Linjie Li, Weikai Huang +8 authors
Imaginative Perception Tokens (IPT) enhance vision-language models' spatial reasoning by providing intermediate perceptual representations that externalize what the model would perceive from alternative viewpoints, outperforming traditional text-based reasoning methods.
SII-GAIR, Sand. ai, Ethan Chern +42 authors
daVinci-MagiHuman is an open-source audio-video generative model that synchronizes text, video, and audio through a single-stream Transformer architecture, achieving high-quality human-centric content generation with efficient inference capabilities.
Orantqing, Shengpeng Ji, Junlong Tong +20 authors
Gander is an end-to-end framework that integrates continuous multi-modal streaming, real-time full-duplex interaction, and agentic reasoning through a Cerebellum-Brain architecture and a chunk-level token stream design.
Zhengxu Yu, Yu Fu, Zhiyuan He +5 authors
OneManCompany (OMC) introduces an organizational framework for multi-agent systems that enables dynamic team assembly, governance, and improvement through portable agent identities and hierarchical decision-making processes.
Issar Tzachor, Dvir Samuel, Rami Ben-Ari
Generative multimodal large language models are adapted for video-text embedding and retrieval through intermediate-layer analysis and text-based alignment without visual supervision.
Yunlong Lin, Zixu Lin, Zhaohu Xing +23 authors
JarvisHub is a canvas-based agent framework that supports sustained, inspectable multimodal creative production through editable project states and progressive agent planning.
Tianyi Zhou, Dongrui Liu, Leitao Yuan +2 authors
Person-grounded AI skills are automatically distilled from heterogeneous traces into inspectable, correctable packages that capture both capabilities and behavioral patterns.
Sen Xu, Shixi Liu, Wei Wang +6 authors
VibeThinker-3B demonstrates that compact models can achieve state-of-the-art performance on verifiable reasoning tasks through specialized training techniques, challenging conventional scaling assumptions.
Bin Wang, Tianyao He, Linke Ouyang +40 authors
Training data engineering and optimized strategies improve document parsing performance without architectural changes, achieving state-of-the-art results on OmniDocBench v1.6.
Mingyu Ouyang, Siyuan Hu, Kevin Qinghong Lin +2 authors
GameWorld presents a standardized benchmark for evaluating multimodal large language model agents in video games, featuring diverse games and verified metrics for comprehensive assessment.
Shaoqiu Zhang, Yuhang Wang, Jialiang Liang +8 authors
SWE-Explore introduces a benchmark for evaluating coding agents' repository exploration capabilities by requiring ranked lists of relevant code regions within line budgets, demonstrating that agentic exploration outperforms traditional retrieval methods.
Qinsi Wang, Hancheng Ye, Jinhee Kim +12 authors
Structure of Thought prompting technique enhances language model performance by guiding explicit intermediate text structuring across diverse tasks, while T2S-Bench benchmark evaluates and improves text-to-structure capabilities with comprehensive scientific domain coverage.
Kangning Zhang, Shuai Shao, Qingyao Li +8 authors
Multimodal procedural knowledge frameworks enable visual agents to leverage external reusable skills through structured representations combining text, state cards, and visual keyframes, improving decision-making in complex environments.
Bowen Ye, Rang Li, Qibin Yang +10 authors
Claw-Eval addresses limitations in agent benchmarks by providing comprehensive evaluation across multiple modalities with trajectory-aware grading and safety assessments.
Zhifei Xie, Zihang Liu, Ze An +8 authors
A unified streaming audio model is developed that combines offline task execution with real-time audio instruction following through an end-to-end framework supporting multiple audio interaction capabilities.
Kou Shi, Zun Wang, Qisheng Su +10 authors
FACET constructs executable terminal tasks by preserving source intent and grounding instructions, solutions, and verifiers in a shared repaired environment to enable scalable agent training.
Boqiang Zhang, Lei Ke, Ruihan Yang +5 authors
Penguin-VL demonstrates that text-only initialized vision encoders can achieve superior performance in multimodal understanding tasks compared to traditional contrastive pretraining methods, enabling efficient deployment on resource-constrained devices.
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