7 papers
Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond
Meng Chu, Xuan Billy Zhang, Kevin Qinghong Lin +47
As AI systems move from generating text to accomplishing goals through sustained interaction, the ability to model environment dynamics becomes a central bottleneck. Agents that ma…
When Continual Learning Moves to Memory: A Study of Experience Reuse in LLM Agents
Qisheng Hu, Quanyu Long, Wenya Wang
Memory-augmented LLM agents offer an appealing shortcut to continual learning: rather than updating model parameters, they accumulate experience in external memory, seemingly sides…
STARE at the Structure: Steering ICL Exemplar Selection with Structural Alignment
Jiaqian Li, Qisheng Hu, Jing Li +1
In-Context Learning (ICL) has become a powerful paradigm that enables LLMs to perform a wide range of tasks without task-specific fine-tuning. However, the effectiveness of ICL hea…
BOOST: Bootstrapping Strategy-Driven Reasoning Programs for Program-Guided Fact-Checking
Qisheng Hu, Quanyu Long, Wenya Wang
Large language model pipelines have improved automated fact-checking for complex claims, yet many approaches rely on few-shot in-context learning with demonstrations that require s…
Coordinating Search-Informed Reasoning and Reasoning-Guided Search in Claim Verification
Qisheng Hu, Quanyu Long, Wenya Wang
Multi-hop claim verification is inherently challenging, requiring multi-step reasoning to construct verification chains while iteratively searching for information to uncover hidde…
Decomposition Dilemmas: Does Claim Decomposition Boost or Burden Fact-Checking Performance?
Qisheng Hu, Quanyu Long, Wenya Wang
Fact-checking pipelines increasingly adopt the Decompose-Then-Verify paradigm, where texts are broken down into smaller claims for individual verification and subsequently combined…