15 papers
Agentic Self-Awareness: Aligning Knowing, Acting, and Holding
Qinglin Chen, Hiroaki Hayashi, Jiaxin Zhang +1
Frontier AI agents increasingly act in environments where seemingly solvable tasks may lack prerequisites, contain conflicting requirements, or reveal blockers only during executio…
GameSmith: Scaling Zero-Sum Self-Play with Synthesised Games
Weixian Waylon Li, Jiaxin Zhang, Han Zhou +4
Post-training large language models (LLMs) on two-player zero-sum games provides a verifiable reward, and the gains have been shown to transfer to general reasoning. Existing pipel…
Fork Where the Model Changes Its Mind: Belief-Shift Branching for Tree-Structured Reinforcement Learning
Bin Lei, Yu Li, Prafulla Kumar Choubey +7
Tree-structured rollouts give critic-free reinforcement learning with verifiable rewards (RLVR) step-level credit: fork a chain at an intermediate point, and sibling outcome differ…
On the Fragility of Self-Improving Agents: Variance, Task Order, and Underspecification
Qinyuan Ye, Yu Li, Yada Pruksachatkun +2
Memory-based self-improving agents--those that learn from an online stream of tasks and improve over time by maintaining a textual memory bank--have shown great promise in recent l…
TRIAGE: Role-Typed Credit Assignment for Agentic Reinforcement Learning
Yuanda Xu, Zhengze Zhou, Hejian Sang +6
Agentic reinforcement learning requires assigning credit to environment-facing actions such as searches, clicks, edits, navigation commands, and object interactions. Standard GRPO…
Speculate with Memory: Lossless Acceleration for LLM Agents
Yu Li, Qinyuan Ye, Prafulla Kumar Choubey +2
Speculative execution accelerates LLM agents by using a smaller, cheaper model to predict and pre-launch the next step while the environment is idle. However, existing speculators…
Dont Stop Early: Scalable Enterprise Deep Research with Controlled Information Flow and Evidence-Aware Termination
Prafulla Kumar Choubey, Kung-Hsiang Huang, Pranav Narayanan Venkit +5
Enterprise deep research often fails to produce decision-ready reports due to uneven information coverage, context explosion, and premature stopping. We propose a scalable Enterpri…
The Illusion of Certainty: Decoupling Capability and Calibration in On-Policy Distillation
Jiaxin Zhang, Xiangyu Peng, Qinglin Chen +3
On-policy distillation (OPD) is an increasingly important paradigm for post-training language models. However, we identify a pervasive Scaling Law of Miscalibration: while OPD effe…
Agentic Confidence Calibration
Jiaxin Zhang, Caiming Xiong, Chien-Sheng Wu
AI agents are rapidly advancing from passive language models to autonomous systems executing complex, multi-step tasks. Yet their overconfidence in failure remains a fundamental ba…
Agentic Uncertainty Quantification
Jiaxin Zhang, Prafulla Kumar Choubey, Kung-Hsiang Huang +2
Although AI agents have demonstrated impressive capabilities in long-horizon reasoning, their reliability is severely hampered by the ``Spiral of Hallucination,'' where early epist…
From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Models
Jiaxin Zhang, Wendi Cui, Zhuohang Li +4
While Large Language Models (LLMs) show remarkable capabilities, their unreliability remains a critical barrier to deployment in high-stakes domains. This survey charts a functiona…
Seeing is Believing? Evaluating Vision-Language Model Susceptibility in Agent-to-Agent Multimodal Persuasion
Haoyi Qiu, Yilun Zhou, Pranav Narayanan Venkit +4
As autonomous agents increasingly interact, they inevitably attempt to influence one another. While prior work in text-only settings has explored the dynamics of Agent-to-Agent (A2…
Nudging the Boundaries of LLM Reasoning
Justin Chih-Yao Chen, Becky Xiangyu Peng, Prafulla Kumar Choubey +4
Current online reinforcement learning (RL) algorithms like GRPO share a key limitation in LLM reasoning: they cannot learn from problems that are "unsolvable" to the model. In othe…
CookBench: A Long-Horizon Embodied Planning Benchmark for Complex Cooking Scenarios
Muzhen Cai, Xiubo Chen, Yining An +5
Embodied Planning is dedicated to the goal of creating agents capable of executing long-horizon tasks in complex physical worlds. However, existing embodied planning benchmarks fre…
CueTip: An Interactive and Explainable Physics-aware Pool Assistant
Sean Memery, Kevin Denamganai, Jiaxin Zhang +3
We present an interactive and explainable automated coaching assistant called CueTip for a variant of pool/billiards. CueTip's novelty lies in its combination of three features: a…