36 citations · 62 across the 32 of their papers we have counts for
13 papers · 1 filter
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,…
VARI: Robust Text-to-Video Generation via Group-Structured Intent Alignment
Mingxuan Zhu, Hohei Chan, Shiyuan Liu +2
Modern text-to-video (T2V) models generate visually compelling videos, yet meaning-preserving changes in prompt wording can substantially alter semantic realization and overall qua…
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…
Hierarchical Data Selection via Manifold Coverage and Sparse Feature Coverage in LLM Post-training
Peng Sun, Yi Yang, Antong Zhang +7
As supervised fine-tuning data continues to scale, selecting high-value subsets from large candidate pools is crucial for reducing training cost and improving model performance. Ex…
Data-DPO: Direct Preference Optimization for Target Model Data Selection in LLM Post-Training
Peng Sun, Yi Yang, Antong Zhang +7
Data selection in supervised fine-tuning aims to select a small set of effective samples from large-scale candidate data, reducing training cost while preserving model performance.…
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…
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…
OmniMatBench: A Human-Calibrated Multimodal Reasoning Benchmark Across 19 Materials Science Subfields
Wanhao Liu, Jiaqing Xie, Qian Tan +10
As multimodal language models play an increasingly important role in scientific research, materials science offers a critical testbed due to its interdisciplinary, multimodal, and…
RTP-LLM: High-Performance Alibaba LLM Inference Engine
Boyu Tan, Jiarui Guo, Zongwei Lv +26
Large Language Models (LLMs) have revolutionized AI applications, but deploying them at scale presents significant challenges. We present RTP-LLM, a high-performance inference engi…
DeepSurvey: Agent-Oriented Automated Survey Generation with Analytical Depth and Citation Reliability
Ziyue Yang, Da Ma, Hanqi Li +8
As scientific literature grows rapidly and research increasingly involves AI agents, automated survey generation has become a key capability for both agents and human researchers.…
Diagnosing CFG Interpretation in LLMs
Hanqi Li, Lu Chen, Kai Yu
As LLMs are increasingly integrated into agentic systems, they must adhere to dynamically defined, machine-interpretable interfaces. We evaluate LLMs as in-context interpreters: gi…
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…