Maligned - October 29, 2025

AI news without the BS

Here’s what actually matters in AI today. No fluff, no hype - just 5 developments worth your time.

Today’s Top 5 AI Developments

1. Agent LLM Unleashed: Tongyi DeepResearch Tackles Complex Info-Seeking 🔍

Alibaba’s new 30.5 billion parameter agentic LLM, Tongyi DeepResearch, is built for serious, long-haul information-seeking. It’s trained end-to-end for deep research tasks, utilizing an innovative self-training data pipeline that doesn’t rely on costly human labels. This model is already crushing benchmarks like Humanity’s Last Exam, pushing the boundaries of autonomous AI agents.

Source: arXiv Link: http://arxiv.org/abs/2510.24701v1

2. Standardizing Agent Data: The Key to Scaling LLM Agents 🔑

Developing effective AI agents has been bottlenecked by fragmented, diverse datasets. The new Agent Data Protocol (ADP) solves this by providing a lightweight, unified “interlingua” for all types of agent training data – from tool use to coding. This protocol has already shown an average performance gain of ~20% for fine-tuning LLM agents, making large-scale agent development finally scalable and reproducible.

Source: arXiv Link: http://arxiv.org/abs/2510.24702v1

3. Flawless Video Paths: Generative View Stitching Eliminates Collision & Jitters 🎥

Video generation often struggles with maintaining consistency, especially with pre-defined camera paths, leading to jarring collisions and loss of coherence. Generative View Stitching (GVS) fixes this by allowing diffusion models to ‘stitch’ together video segments, conditioning on both past and future frames. The result? Stable, collision-free, and temporally consistent video, even for complex paths like impossible staircases.

Source: arXiv Link: http://arxiv.org/abs/2510.24718v1

4. Vision Transformers Understand Objects (Naturally) 🧠

Forget what you heard about ViTs lacking object understanding. New research shows that self-supervised Vision Transformers naturally learn to bind features into coherent objects – a core human cognitive ability. This “IsSameObject” signal emerges reliably and actively guides attention, proving ViTs are more sophisticated than previously thought and opening doors for more robust vision models.

Source: arXiv Link: http://arxiv.org/abs/2510.24709v1

5. Reality Check: LLMs Still Fumble VR Game Control 🎮 (No BS)

While LLMs are amazing at language, translating semantic actions into precise physical device manipulations, like playing VR games, is still a major hurdle. ComboBench, a new benchmark, reveals even top models like Gemini 1.5 Pro and GPT-4o struggle with the procedural and spatial reasoning needed for VR. It’s a blunt reminder that embodied AI still has a long way to go from high-level commands to real-world dexterity.

Source: arXiv Link: http://arxiv.org/abs/2510.24706v1

That’s it for today. Stay aligned. 🎯

Maligned - AI news without the BS