18 citations · 135 across the 104 of their papers we have counts for
6 papers · 1 filter
Learn Now, Use Next, Trust Later: Prequential Test-Time Learning for LLM Agents
Tong Zhao, Reed Li, Yuyang Hu +5
Adapting large language model agents during deployment requires not only retaining past experience, but also turning new observations into timely guidance. Many test-time learning…
GPG: Generalized Policy Gradient Theorem for Transformer-based Policies
Hangyu Mao, Guangting Dong, Zhicheng Dou
We present the Generalized Policy Gradient (GPG) Theorem, specifically designed for Transformer-based policies. Notably, we demonstrate that both standard Policy Gradient Theorem a…
Agentic Entropy-Balanced Policy Optimization
Guanting Dong, Licheng Bao, Zhongyuan Wang +11
Recently, Agentic Reinforcement Learning (Agentic RL) has made significant progress in incentivizing the multi-turn, long-horizon tool-use capabilities of web agents. While mainstr…
Harness Local Rewards for Global Benefits: Effective Text-to-Video Generation Alignment with Patch-level Reward Models
Shuting Wang, Haihong Tang, Zhicheng Dou +1
The emergence of diffusion models (DMs) has significantly improved the quality of text-to-video generation models (VGMs). However, current VGM optimization primarily emphasizes the…
Disentangled Hyperbolic Representation Learning for Heterogeneous Graphs
Qijie Bai, Changli Nie, Haiwei Zhang +2
Heterogeneous graphs have attracted a lot of research interests recently due to the success for representing complex real-world systems. However, existing methods have two pain poi…
Less is More: Pre-train a Strong Text Encoder for Dense Retrieval Using a Weak Decoder
Shuqi Lu, Di He, Chenyan Xiong +6
Dense retrieval requires high-quality text sequence embeddings to support effective search in the representation space. Autoencoder-based language models are appealing in dense ret…