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ERNIE 5.0 Technical Report

Intermediate
Haifeng Wang, Hua Wu et al.Feb 4arXiv

ERNIE 5.0 is a single giant model that can read and create text, images, video, and audio by predicting the next pieces step by step, like writing a story one line at a time.

#ERNIE 5.0#unified autoregressive model#mixture-of-experts

WideSeek-R1: Exploring Width Scaling for Broad Information Seeking via Multi-Agent Reinforcement Learning

Intermediate
Zelai Xu, Zhexuan Xu et al.Feb 4arXiv

WideSeek-R1 teaches a small 4B-parameter language model to act like a well-run team: one leader plans, many helpers work in parallel, and everyone learns together with reinforcement learning.

#width scaling#multi-agent reinforcement learning#orchestration

LycheeDecode: Accelerating Long-Context LLM Inference via Hybrid-Head Sparse Decoding

Intermediate
Gang Lin, Dongfang Li et al.Feb 4arXiv

Long texts make language models slow because they must keep and re-check a huge memory called the KV cache for every new word they write.

#long-context LLM#sparse attention#head specialization

EgoActor: Grounding Task Planning into Spatial-aware Egocentric Actions for Humanoid Robots via Visual-Language Models

Intermediate
Yu Bai, MingMing Yu et al.Feb 4arXiv

EgoActor is a vision-language model that turns everyday instructions like 'Go to the door and say hi' into step-by-step, egocentric actions a humanoid robot can actually do.

#EgoActing#vision-language model#humanoid robot

Beyond Unimodal Shortcuts: MLLMs as Cross-Modal Reasoners for Grounded Named Entity Recognition

Intermediate
Jinlong Ma, Yu Zhang et al.Feb 4arXiv

The paper teaches multimodal large language models (MLLMs) to stop guessing from just text or just images and instead check both together before answering.

#GMNER#Multimodal Large Language Models#Modality Bias

Agent-Omit: Training Efficient LLM Agents for Adaptive Thought and Observation Omission via Agentic Reinforcement Learning

Intermediate
Yansong Ning, Jun Fang et al.Feb 4arXiv

Agent-Omit teaches AI agents to skip unneeded thinking and old observations, cutting tokens while keeping accuracy high.

#LLM agents#reinforcement learning#agentic RL

Steering LLMs via Scalable Interactive Oversight

Intermediate
Enyu Zhou, Zhiheng Xi et al.Feb 4arXiv

The paper tackles a common problem: people can ask AI to do big, complex tasks, but they can’t always explain exactly what they want or check the results well.

#scalable oversight#interactive alignment#requirement elicitation

Training Data Efficiency in Multimodal Process Reward Models

Intermediate
Jinyuan Li, Chengsong Huang et al.Feb 4arXiv

Multimodal Process Reward Models (MPRMs) teach AI to judge each step of a picture-and-text reasoning process, not just the final answer.

#Multimodal Process Reward Model#Process Supervision#Monte Carlo Annotation

VLS: Steering Pretrained Robot Policies via Vision-Language Models

Intermediate
Shuo Liu, Ishneet Sukhvinder Singh et al.Feb 3arXiv

Robots often learn good hand motions during training but get confused when the scene or the instructions change at test time, even a little bit.

#Vision–Language Steering#Inference-time control#Diffusion policy

AgentArk: Distilling Multi-Agent Intelligence into a Single LLM Agent

Intermediate
Yinyi Luo, Yiqiao Jin et al.Feb 3arXiv

AgentArk teaches one language model to think like a whole team of models that debate, so it can solve tough problems quickly without running a long, expensive debate at answer time.

#multi-agent distillation#process reward model#GRPO

Parallel-Probe: Towards Efficient Parallel Thinking via 2D Probing

Intermediate
Tong Zheng, Chengsong Huang et al.Feb 3arXiv

Parallel-Probe is a simple add-on that lets many AI “thought paths” think at once but stop early when they already agree.

#parallel thinking#2D probing#consensus-based early stopping

AutoFigure: Generating and Refining Publication-Ready Scientific Illustrations

Intermediate
Minjun Zhu, Zhen Lin et al.Feb 3arXiv

AutoFigure is an AI system that reads long scientific texts and then thinks, plans, and draws clear, good-looking figures—like a careful student who makes a neat, accurate poster from a long chapter.

#AutoFigure#FigureBench#Reasoned Rendering
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