activity
20232026
most citedA Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Models

188 citations · 263 across the 12 of their papers we have counts for

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Showing 2026Show all

7 papers · 1 filter

cs.CL2026

DVBench: Benchmarking MLLMs for Understanding Dynamic Charts and Narratives in Data Videos

Bomiao Wang, Zekai Shao, Jiexiang Lan +3

While MLLMs have made significant strides in chart comprehension and video understanding, current evaluations largely isolate these capabilities, leaving a critical gap in understa…

cs.HC2026

DeepConnect: A Visual Analytics System for Bridging Interdisciplinary Research Collaborations

Yingchaojie Feng, Zekai Shao, Yiqun Sun +2

Interdisciplinary research collaboration is crucial for scientific innovation, but it remains difficult to initiate in practice. Existing collaborator discovery approaches are ofte…

cs.AI2026

ChartAnno: Benchmarking Multimodal Large Language Models for Chart Annotation Generation

Zhenghan Chen, Zekai Shao, Lidan Tan +10

Annotations are essential to communicative visualization, helping explain data, emphasize key findings, and guide attention. While multimodal large language models (MLLMs) offer ne…

cs.CL2026

ChartFI: Benchmarking Faithfulness and Insightfulness of Chart Descriptions from Multimodal Large Language Models

Fen Wang, Zekai Shao, Qiman Kang +5

Chart descriptions are essential for accessibility, cross-modal retrieval, and assisting readers in extracting insights from complex visualizations. As multimodal large language mo…

cs.LG2026

From to : Taming Divergence in Soft Clipping via Bilateral Decoupled Decay of Probability Gradient Weight

Xiaoliang Fu, Jiaye Lin, Yangyi Fang +6

Reinforcement Learning with Verifiable Rewards (RLVR) has catalyzed a leap in Large Language Model (LLM) reasoning, yet its optimization dynamics remain fragile. Standard algorithm…

cs.HC2026

NotebookRAG: Retrieving Multiple Notebooks to Augment the Generation of EDA Notebooks for Crowd-Wisdom

Yi Shan, Yixuan He, Zekai Shao +2

High-quality exploratory data analysis (EDA) is essential in the data science pipeline, but remains highly dependent on analysts' expertise and effort. While recent LLM-based appro…

cs.LG2026

MASPO: Unifying Gradient Utilization, Probability Mass, and Signal Reliability for Robust and Sample-Efficient LLM Reasoning

Xiaoliang Fu, Jiaye Lin, Yangyi Fang +7

Existing Reinforcement Learning with Verifiable Rewards (RLVR) algorithms, such as GRPO, rely on rigid, uniform, and symmetric trust region mechanisms that are fundamentally misali…