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Zihan Ma

8 accepted papers

2026

Splat-SAP: Feed-Forward Gaussian Splatting for Human-Centered Scene with Scale-Aware Point Map Reconstruction

AAAI 2026technical

We present Splat-SAP, a feed-forward approach to render novel views of human-centered scenes from binocular cameras with large sparsity. Gaussian Splatting has shown its promising potential in rendering tasks, but it typically necessitates per-scene optimization with dense input views. Although some

Cited by 0SourcePDFScholar
2026

TrajEvo: Trajectory Prediction Heuristics Design via LLM-driven Evolution

AAAI 2026technical

Trajectory prediction is a crucial task in modeling human behavior, especially in safety-critical fields such as social robotics and autonomous vehicle navigation. Traditional heuristics based on handcrafted rules often lack accuracy, while recently proposed deep learning approaches suffer from comp

Cited by 0SourcePDFScholar
2025

Each Fake News Is Fake in Its Own Way: An Attribution Multi-Granularity Benchmark for Multimodal Fake News Detection

AAAI 2025technical

Social platforms, while facilitating access to information, have also become saturated with a plethora of fake news, resulting in negative consequences. Automatic multimodal fake news detection is a worthwhile pursuit. Existing multimodal fake news datasets only provide binary labels of real or fake…

2025

How Do Social Bots Participate in Misinformation Spread? A Comprehensive Dataset and Analysis

EMNLP 2025

Social media platforms provide an ideal environment to spread misinformation, where social bots can accelerate the spread. This paper explores the interplay between social bots and misinformation on the Sina Weibo platform. We construct a large-scale dataset that includes annotations for both misinf

Cited by 0SourcePDFScholar
2025

IMOL: Incomplete-Modality-Tolerant Learning for Multi-Domain Fake News Video Detection

ACL 2025long

While recent advances in fake news video detection have shown promising potential, existing approaches typically (1) focus on a specific domain (e.g., politics) and (2) assume the availability of multiple modalities, including video, audio, description texts, and related images. However, these metho…

Cited by 0SourcePDFScholar
2025

Rethinking Verification for LLM Code Generation: From Generation to Testing

NeurIPS 2025poster

Large language models (LLMs) have recently achieved notable success in code‑generation benchmarks such as HumanEval and LiveCodeBench. However, a detailed examination reveals that these evaluation suites often comprise only a limited number of homogeneous test cases, resulting in subtle faults going…

Cited by 0SourcecodeScholar
2024

Event-Radar: Event-driven Multi-View Learning for Multimodal Fake News Detection

ACL 2024long

The swift detection of multimedia fake news has emerged as a crucial task in combating malicious propaganda and safeguarding the security of the online environment. While existing methods have achieved commendable results in modeling entity-level inconsistency, addressing event-level inconsistency f…

Cited by 11SourcePDFScholar
2022

TwiBot-22: Towards Graph-Based Twitter Bot Detection

NeurIPS 2022accept

Twitter bot detection has become an increasingly important task to combat misinformation, facilitate social media moderation, and preserve the integrity of the online discourse. State-of-the-art bot detection methods generally leverage the graph structure of the Twitter network, and they exhibit pro…