1 citations · 1 across the 10 of their papers we have counts for
10 papers
Blockwise Policy-Drift Gating for On-Policy Distillation
Liwen Zheng, Haiyun Jiang
On-policy distillation (OPD) trains a student policy using teacher signals computed on trajectories sampled by the student itself. Recent work shows that sampled-token OPD can be f…
Where and How to Prune: An Empirical Study of Visual Token Pruning for GUI Agent Navigation
Daiqiang Li, Zihao Pan, Zeyu Zhang +8
In recent years, GUI agents have demonstrated strong potential in navigation tasks. However, preserving complete historical screenshots introduces substantial computational overhea…
AerialMind: Towards Referring Multi-Object Tracking in UAV Scenarios
Chenglizhao Chen, Shaofeng Liang, Runwei Guan +6
Referring Multi-Object Tracking (RMOT) aims to achieve precise object detection and tracking through natural language instructions, representing a fundamental capability for intell…
ARK: Answer-Centric Retriever Tuning via KG-augmented Curriculum Learning
Hang Ding, Jiawei Zhou, Haiyun Jiang
Retrieval-Augmented Generation (RAG) has emerged as a powerful framework for knowledge-intensive tasks, yet its effectiveness in long-context scenarios is often bottlenecked by the…
MaLoRA: Gated Modality LoRA for Key-Space Alignment in Multimodal LLM Fine-Tuning
Xinhan Zheng, Huyu Wu, Xueting Wang +2
Multimodal large language models (MLLMs) exhibit a pronounced preference for textual inputs when processing vision-language data, limiting their ability to reason effectively from…
When Language Overrules: Revealing Text Dominance in Multimodal Large Language Models
Huyu Wu, Meng Tang, Xinhan Zheng +1
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities across a diverse range of multimodal tasks. However, these models suffer from a core problem know…
Vision-EKIPL: External Knowledge-Infused Policy Learning for Visual Reasoning
Chaoyang Wang, Zeyu Zhang, Meng Meng +2
Visual reasoning is crucial for understanding complex multimodal data and advancing Artificial General Intelligence. Existing methods enhance the reasoning capability of Multimodal…
Empowering Users in Digital Privacy Management through Interactive LLM-Based Agents
Bolun Sun, Yifan Zhou, Haiyun Jiang
This paper presents a novel application of large language models (LLMs) to enhance user comprehension of privacy policies through an interactive dialogue agent. We demonstrate that…
MIKE: A New Benchmark for Fine-grained Multimodal Entity Knowledge Editing
Jiaqi Li, Miaozeng Du, Chuanyi Zhang +6
Multimodal knowledge editing represents a critical advancement in enhancing the capabilities of Multimodal Large Language Models (MLLMs). Despite its potential, current benchmarks…
MR-GSM8K: A Meta-Reasoning Benchmark for Large Language Model Evaluation
Zhongshen Zeng, Pengguang Chen, Shu Liu +2
In this work, we introduce a novel evaluation paradigm for Large Language Models (LLMs) that compels them to transition from a traditional question-answering role, akin to a studen…