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HY3D-Bench: Generation of 3D Assets

Intermediate

Team Hunyuan3D, : et al.Feb 3arXiv

HY3D-Bench is a complete, open-source “starter kit” for making and studying high-quality 3D objects.

#HY3D-Bench#watertight meshes#part-level decomposition

HySparse: A Hybrid Sparse Attention Architecture with Oracle Token Selection and KV Cache Sharing

Intermediate

Yizhao Gao, Jianyu Wei et al.Feb 3arXiv

HySparse is a new way for AI models to pay attention that mixes a few full attention layers with many fast, memory‑saving sparse layers.

#Hybrid Sparse Attention#Oracle Token Selection#KV Cache Sharing

Semantic Routing: Exploring Multi-Layer LLM Feature Weighting for Diffusion Transformers

Intermediate

Bozhou Li, Yushuo Guan et al.Feb 3arXiv

The paper shows that using information from many layers of a language model (not just one) helps text-to-image diffusion transformers follow prompts much better.

#Diffusion Transformer#Text Conditioning#Multi-layer LLM Features

A-RAG: Scaling Agentic Retrieval-Augmented Generation via Hierarchical Retrieval Interfaces

Intermediate

Mingxuan Du, Benfeng Xu et al.Feb 3arXiv

A-RAG lets the AI choose how to search, what to read, and when to stop, instead of following a fixed recipe.

#Agentic RAG#Hierarchical Retrieval Interfaces#Keyword Search

SWE-World: Building Software Engineering Agents in Docker-Free Environments

Intermediate

Shuang Sun, Huatong Song et al.Feb 3arXiv

SWE-World lets code-fixing AI agents practice and learn without heavy Docker containers by using smart models that pretend to be the computer and tests.

#SWE-World#software engineering agents#Docker-free training

SWE-Master: Unleashing the Potential of Software Engineering Agents via Post-Training

Intermediate

Huatong Song, Lisheng Huang et al.Feb 3arXiv

SWE-Master is a fully open, step-by-step recipe for turning a regular coding model into a strong software-fixing agent that works across many steps, files, and tests.

#SWE-Master#software engineering agent#long-horizon SFT

MeKi: Memory-based Expert Knowledge Injection for Efficient LLM Scaling

Intermediate

Ning Ding, Fangcheng Liu et al.Feb 3arXiv

MeKi is a new way to grow a language model’s knowledge by using storage (ROM) instead of extra heavy calculations (FLOPs).

#MeKi#memory-based scaling#token-level experts

Accurate Failure Prediction in Agents Does Not Imply Effective Failure Prevention

Intermediate

Rakshith Vasudev, Melisa Russak et al.Feb 3arXiv

The paper shows that even if a model is great at predicting when an AI agent will fail, jumping in to “fix” the agent mid-task can still make things worse.

#LLM critic#execution-time intervention#disruption–recovery tradeoff

Token Sparse Attention: Efficient Long-Context Inference with Interleaved Token Selection

Intermediate

Dongwon Jo, Beomseok Kang et al.Feb 3arXiv

This paper speeds up how AI models read very long texts by carefully choosing which words (tokens) to focus on at each step.

#Token Sparse Attention#Dynamic Token Coverage#Representation Drift

Privasis: Synthesizing the Largest "Public" Private Dataset from Scratch

Intermediate

Hyunwoo Kim, Niloofar Mireshghallah et al.Feb 3arXiv

The paper introduces PRIVASIS, a huge, fully synthetic dataset (1.4 million records) filled with realistic-looking private details, but created from scratch so it does not belong to any real person.

#synthetic dataset#privacy preservation#data sanitization

FASA: Frequency-aware Sparse Attention

Intermediate

Yifei Wang, Yueqi Wang et al.Feb 3arXiv

FASA is a training-free method that makes large language models faster and lighter on memory by keeping only the most useful past tokens during decoding.

#FASA#Frequency-aware sparse attention#KV cache compression

Self-Hinting Language Models Enhance Reinforcement Learning

Intermediate

Baohao Liao, Hanze Dong et al.Feb 3arXiv

When rewards are rare, a popular training method for language models (GRPO) often stops learning because every try in a group gets the same score, so there is nothing to compare.

#reinforcement learning#GRPO#self-hinting

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