Author

Jie Gao

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Preprint Oct 2026

FastJEV: Understanding Redundancy for Compact JEV Inference

JEV models make multimodal decisions by directly scoring candidates. Although the common context is encoded once, candidate evaluation can still repeat matching token histories, duplicate inference states, and execute the full backbone. In this paper, we study these sources of redundancy and present FastJEV for compact...

Jie Ma, Jie Gao, Yi-Hang Liu et al. · 0 citations

#artificial intelligence Preprint Oct 2026

Accurate but Not Humble: Evaluating Epistemic Humility in LLM Agents under Knowledge Conflict

When retrieved evidence contradicts an agent's prior beliefs, does it revise its answer, acknowledge uncertainty, or persist with an incorrect conclusion? Existing evaluations of agentic systems focus primarily on task success, offering limited insight into how agents handle such conflicts. We propose to evaluate agent...

Kaiser Sun, Bernal Jiménez Gutiérrez, Hong-Jun Liu et al. · 0 citations

#natural language process... Preprint Sep 2026

On the Behavioral Traits of LLM Agents

This work proposes A-B-D to infer traits bottom-up from behavioral data (B-data), namely how agents act on their environment and communicate with users, as recorded in existing trajectories, and offers a new lens for understanding AI personality.

Hao-Kai Zhao, Jie Gao, Yunze Xiao et al. · 0 citations

#natural language process... Preprint Sep 2026

Where Does Retrieval-Based Open-Ended Evaluation Fail? Automatic Taxonomy Induction from Long-Form Medical Answer Factuality Verification

Analysis reveals that scaling model size, adding reasoning effort, expanding to authoritative web sources, and applying medical fine-tuning do not resolve these failure modes, demonstrating that they represent fundamental limitations of the retrieve-then-verify paradigm in open-ended medical settings rather than artifa...

He-Yuan Huang, Ji Dai, Alexandra DeLucia et al. · 0 citations

Jul 2026

Beyond Borrowed Histories: Person-Aligned User Simulation for Interactive Role-Playing Evaluation

PALATE (Person-Aligned LLM-Simulated-User Assessment with Tailored Evaluation with Tailored Evaluation), a scalable RPA benchmark built on user simulators, produces interpretable evaluations of specific user-RPA pairs rather than compressing systems into a single user-independent ranking.

Yuhan Zhu, Ming-Xuan Du, Benfeng Xu et al. · arXiv.org · 0 citations

#artificial intelligence Preprint Aug 2026

Using Grounded Theory for Agent Behavior Analysis at Scale

This work proposes AutoTraceGT (Automated Trace analysis through Grounded Theory), the first multi-agent pipeline that automates grounded theory on agent trajectories and suggests Grounded Theory offers a scalable analytic tool for ML researchers and agent developers studying what agents actually do.

Zhuo-Ran Lu, Yang-Yang Yu, Zhuo-Yan Li et al. · 0 citations

Jul 2026

Capturing Token Tendencies for Training-Free Token Pruning in Multimodal Large Language Models

Trend-aware Pruning is proposed, a novel framework that elevates pruning from a local snapshot decision to a temporal trajectory modeling problem, and enables a dynamic rectification mechanism that selectively reactivates "late-blooming" tokens, those initially undervalued but exhibiting rising semantic importance, the...

Jie Ma, Zhike Qiu, Jie Gao et al. · arXiv.org · 0 citations