Papers1252

MIBURI: Towards Expressive Interactive Gesture Synthesis

M. Hamza Mughal, Rishabh Dabral et al.Mar 3arXiv

MIBURI is a system that makes a talking digital character move its body and face expressively in real time while it speaks.

#co-speech gesture synthesis#embodied conversational agents#causal generation

CFG-Ctrl: Control-Based Classifier-Free Diffusion Guidance

Intermediate

Hanyang Wang, Yiyang Liu et al.Mar 3arXiv

This paper turns a popular image-guidance trick (Classifier-Free Guidance) into a feedback-control problem, just like keeping a car steady in its lane.

#Classifier-Free Guidance#Sliding Mode Control#Diffusion Models

Beyond Language Modeling: An Exploration of Multimodal Pretraining

Intermediate

Shengbang Tong, David Fan et al.Mar 3arXiv

The paper trains one model from scratch to both read text and see images/videos, instead of starting from a language-only model.

#multimodal pretraining#representation autoencoder#RAE

UniG2U-Bench: Do Unified Models Advance Multimodal Understanding?

Intermediate

Zimo Wen, Boxiu Li et al.Mar 3arXiv

This paper builds UniG2U-Bench, a big test to find out when making pictures (generation) actually helps models understand pictures and text together.

#Unified multimodal models#Vision-language models#Generation-to-Understanding (G2U)

Learning When to Act or Refuse: Guarding Agentic Reasoning Models for Safe Multi-Step Tool Use

Intermediate

Aradhye Agarwal, Gurdit Siyan et al.Mar 3arXiv

Agentic AIs don’t just chat; they plan, use tools, and take many steps, so one wrong click can cause real harm.

#MOSAIC#agentic safety#plan-check-act

Code2Math: Can Your Code Agent Effectively Evolve Math Problems Through Exploration?

Intermediate

Dadi Guo, Yuejin Xie et al.Mar 3arXiv

This paper shows that code-writing AI agents can take an existing math problem and automatically turn it into a new, harder one while keeping it solvable.

#code agents#multi-agent systems#mathematical reasoning

Specificity-aware reinforcement learning for fine-grained open-world classification

Intermediate

Samuele Angheben, Davide Berasi et al.Mar 3arXiv

This paper teaches AI to name things in pictures very specifically (like “golden retriever” instead of just “dog”) without making more mistakes.

#open-world classification#fine-grained recognition#large multimodal models

Chain of World: World Model Thinking in Latent Motion

Intermediate

Fuxiang Yang, Donglin Di et al.Mar 3arXiv

Robots learn better when they think about how things move over time, not by redrawing every pixel of a video.

#Vision-Language-Action#World Model#Latent Motion

BeyondSWE: Can Current Code Agent Survive Beyond Single-Repo Bug Fixing?

Intermediate

Guoxin Chen, Fanzhe Meng et al.Mar 3arXiv

BeyondSWE is a new benchmark that tests code agents on tougher, more real-life tasks than single-repo bug fixing.

#BeyondSWE#code agents#software engineering benchmark

NOVA: Sparse Control, Dense Synthesis for Pair-Free Video Editing

Intermediate

Tianlin Pan, Jiayi Dai et al.Mar 3arXiv

NOVA is a new video editor that lets you change a few key frames (sparse control) while it carefully keeps the original motion and background details (dense synthesis).

#video editing#pair-free training#sparse control

Next Embedding Prediction Makes World Models Stronger

Intermediate

George Bredis, Nikita Balagansky et al.Mar 3arXiv

NE-Dreamer is a model-based reinforcement learning agent that skips rebuilding pixels and instead learns by predicting the next step’s hidden features.

#model-based reinforcement learning#world models#next-embedding prediction

DREAM: Where Visual Understanding Meets Text-to-Image Generation

Beginner

Chao Li, Tianhong Li et al.Mar 3arXiv

DREAM is one model that both understands images (like CLIP) and makes images from text (like top text-to-image models).

#DREAM#contrastive learning#masked autoregressive modeling

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