7 citations · 7 across the 9 of their papers we have counts for
5 papers · 1 filter
AgentSkiller: Scaling Generalist Agent Intelligence through Semantically Integrated Cross-Domain Data Synthesis
Zexu Sun, Bokai Ji, Hengyi Cai +4
Large Language Model agents demonstrate potential in solving real-world problems via tools, yet generalist intelligence is bottlenecked by scarce high-quality, long-horizon data. E…
Internalizing LLM Reasoning via Discovery and Replay of Latent Actions
Zhenning Shi, Yijia Zhu, Junhan Shi +3
The internalization of chain-of-thought processes into hidden states has emerged as a highly efficient paradigm for scaling test-time compute. However, existing activation steering…
Self-Rewarding Sequential Monte Carlo for Masked Diffusion Language Models
Ziwei Luo, Ziqi Jin, Lei Wang +2
This work presents self-rewarding sequential Monte Carlo (SMC), an inference-time scaling algorithm enabling effective sampling of masked diffusion language models (MDLMs). Our alg…
How Order-Sensitive Are LLMs? OrderProbe for Deterministic Structural Reconstruction
Zhaolu Kang, Yingjie He, Kehan Jiang +18
Large language models (LLMs) excel at semantic understanding, yet their ability to reconstruct internal structure from scrambled inputs remains underexplored. Sentence-level restor…
LEAPS: An LLM-Empowered Adaptive Plugin in Taobao AI Search
Lei Wang, Jinhang Wu, Zhibin Wang +1
The rapid rise of large language models has shifted user search behavior from discrete keywords to natural-language, multi-constraint queries--a shift existing e-commerce search ar…