Tracked topic
Qwen3 is an AI model family developed by Alibaba, released as a set of large language models for natural-language tasks.
…A tiny recurrent agent (green) extrapolates the performance at test time. Even with task-specific training, the global model (Qwen) still breaks out-of-distribution. The failure has a name: global shortcuts…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Understanding chart and table images is essential for applying vision-language models (VLMs) to real-world document understanding. While English benchmark s have advanced…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Spatial reasoning is a fundamental capability for vision-language models (VLMs) deployed in real-world environments. However, visual observations are inherently limited representations of…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Recent advances in agentic Reinforcement Learning (RL) have substantially improved the multi-turn tool-use capabilities of large language model agents. However, most existing…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Token-level credit assignment remains a key obstacle for reinforcement learning (RL) in large language models (LLMs), where RL recipes typically treat all tokens…
…Generates nine instructions per scene with Qwen3-8B-VL , split into easy, medium, and hard tiers that progressively test single-goal localization, compositional spatial grounding, and multi-step interaction-aware planning. ⚖️ 𝑷𝒐𝒊𝒏𝒕𝒘𝒊𝒔𝒆…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Although Large Language Model (LLM) agents have demonstrated strong performance on complex tasks, their learning is often limited by inefficient interaction feedback and static…
…To prevent repeated local updates from causing skill drift, SKILL-KD further maintains trace-linked edit histories and performs Drift-Aware Skill Consolidation , deciding whether each patch should add a new rule…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Holistic visual tokenizers are fundamental to unified multimodal models (UMMs) as they map diverse visual inputs into a unified representation space. In this paper…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Dense self-attention is the compute and quality bottleneck of long-video diffusion inference: cost grows quadratically with the sequence length, and beyond the…