36 citations · 66 across the 22 of their papers we have counts for
24 papers
ARGUS: An Agenda-Driven Framework for Reliable User Simulation
Hang Zheng, Nan Jiang, Zichen Zhu +6
High-fidelity user simulators are essential for evaluating and training agents in interactive environments. However, current LLM-based simulators struggle with reliability issues,…
LigBench: A Unified and Human-Aligned Benchmark for LLM-based Research Idea Generation
Chenrun Wang, Mingxuan Zhu, Tiancheng Huang +6
With the rapid advancement of large language models (LLMs), research idea generation has attracted increasing attention. Existing approaches enable LLMs to retrieve relevant litera…
Making AI Scientists Auditable from Evidence to Claim
Zijian Wang, Hanqi Li, Ziyue Yang +17
AI research systems can report improved results without establishing that the tested implementation matches the method described in their conclusions. We introduce Xcientist, a res…
One Student, Many Teachers: Multi-Task On-Policy Distillation via Soft-Prompt Privileged Context
Yingzi Ma, Zichen Zhu, Ming Jiang +1
On-policy self-distillation (OPSD) teaches large language models new skills through a teacher that shares the student's backbone and supervises its own rollouts. Existing teachers…
SSR: Can Simulated Patients Learn to Stigmatize Themselves? Modeling Self-Stigma through Internal Monologue
Kunyao Lan, Bingrui Jin, Zichen Zhu +1
Simulating patients with large language models (LLMs) is a promising tool for mental health training, but existing approaches fail to capture a key clinical reality: self-stigma. P…
IEA: Amateur-Friendly Conversational Image Editing Agent via Three Stages of Multitask Alignment
Zichen Zhu, Yuheng Sun, Mingxuan Zhu +11
Current image editing software often hinges on fixed filters or expert tuning, leaving a gap between amateur users' intent and outcomes. Creations by generative models may contain…
Perceive Before Reasoning: A Pre-Reasoning Perception Framework for Efficient and Reliable Proactive Mobile Agents
Zhijie Ding, Weinan Hong, Zicheng Zhu +6
Multimodal large language models (MLLMs) have substantially advanced mobile agents, yet proactive mobile assistance remains challenging because agents must decide when to intervene…
CharTool: Tool-Integrated Visual Reasoning for Chart Understanding
Situo Zhang, Yifan Zhang, Zichen Zhu +6
Charts are ubiquitous in scientific and financial literature for presenting structured data. However, chart reasoning remains challenging for multimodal large language models (MLLM…
PACER: Blockwise Pre-verification for Speculative Decoding with Adaptive Length
Situo Zhang, Yifan Zhang, Zichen Zhu +5
Speculative decoding (SD) is a powerful technique for accelerating the inference process of large language models (LLMs) without sacrificing accuracy. Typically, SD employs a small…
ChemDFM-R: A Chemical Reasoning LLM Enhanced with Atomized Chemical Knowledge
Zihan Zhao, Ziping Wan, Lu Chen +12
Atomized chemical knowledge, such as functional group information of molecules and reactions, plays a pivotal intermediate role in the reasoning process that connects molecular str…
RetroDFM-R: Reasoning-Driven Retrosynthesis Prediction with Large Language Models via Reinforcement Learning
Situo Zhang, Hanqi Li, Lu Chen +7
Retrosynthetic planning is a cornerstone of organic synthesis and drug discovery. Yet existing AI methods often rely on pattern matching rather than transferable chemical reasoning…
ProgRM: Build Better GUI Agents with Progress Rewards
Danyang Zhang, Situo Zhang, Ziyue Yang +5
LLM-based (Large Language Model) GUI (Graphical User Interface) agents can potentially reshape our daily lives significantly. However, current LLM-based GUI agents suffer from the…
Delusions of Large Language Models
Hongshen Xu, Zixv yang, Zichen Zhu +7
Large Language Models often generate factually incorrect but plausible outputs, known as hallucinations. We identify a more insidious phenomenon, LLM delusion, defined as high beli…
Alignment for Efficient Tool Calling of Large Language Models
Hongshen Xu, Zihan Wang, Zichen Zhu +4
Recent advancements in tool learning have enabled large language models (LLMs) to integrate external tools, enhancing their task performance by expanding their knowledge boundaries…
AdaEAGLE: Optimizing Speculative Decoding via Explicit Modeling of Adaptive Draft Structures
Situo Zhang, Hankun Wang, Da Ma +4
Speculative Decoding (SD) is a popular lossless technique for accelerating the inference of Large Language Models (LLMs). We show that the decoding speed of SD frameworks with stat…
Depression Diagnosis Dialogue Simulation: Self-improving Psychiatrist with Tertiary Memory
Kunyao Lan, Bingrui Jin, Zichen Zhu +4
Mental health issues, particularly depressive disorders, present significant challenges in contemporary society, necessitating the development of effective automated diagnostic met…
MobA: Multifaceted Memory-Enhanced Adaptive Planning for Efficient Mobile Task Automation
Zichen Zhu, Hao Tang, Yansi Li +13
Existing Multimodal Large Language Model (MLLM)-based agents face significant challenges in handling complex GUI (Graphical User Interface) interactions on devices. These challenge…
ChemDFM-X: Towards Large Multimodal Model for Chemistry
Zihan Zhao, Bo Chen, Jingpiao Li +10
Rapid developments of AI tools are expected to offer unprecedented assistance to the research of natural science including chemistry. However, neither existing unimodal task-specif…
Rejection Improves Reliability: Training LLMs to Refuse Unknown Questions Using RL from Knowledge Feedback
Hongshen Xu, Zichen Zhu, Situo Zhang +4
Large Language Models (LLMs) often generate erroneous outputs, known as hallucinations, due to their limitations in discerning questions beyond their knowledge scope. While address…
Hierarchical Multimodal Pre-training for Visually Rich Webpage Understanding
Hongshen Xu, Lu Chen, Zihan Zhao +4
The growing prevalence of visually rich documents, such as webpages and scanned/digital-born documents (images, PDFs, etc.), has led to increased interest in automatic document und…
MULTI: Multimodal Understanding Leaderboard with Text and Images
Zichen Zhu, Yang Xu, Lu Chen +11
The rapid development of multimodal large language models (MLLMs) raises the question of how they compare to human performance. While existing datasets often feature synthetic or o…
Developing ChemDFM as a large language foundation model for chemistry
Zihan Zhao, Da Ma, Lu Chen +11
Artificial intelligence (AI) has played an increasingly important role in chemical research. However, most models currently used in chemistry are specialist models that require tra…
META-GUI: Towards Multi-modal Conversational Agents on Mobile GUI
Liangtai Sun, Xingyu Chen, Lu Chen +3
Task-oriented dialogue (TOD) systems have been widely used by mobile phone intelligent assistants to accomplish tasks such as calendar scheduling or hotel reservation. Current TOD…
Rb-PaStaNet: A Few-Shot Human-Object Interaction Detection Based on Rules and Part States
Shenyu Zhang, Zichen Zhu, Qingquan Bao
Existing Human-Object Interaction (HOI) Detection approaches have achieved great progress on nonrare classes while rare HOI classes are still not well-detected. In this paper, we i…