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Junqi Liu

7 accepted papers

2026

Automated Formal Proofs of Combinatorial Identities via Wilf–Zeilberger Guidance and LLMs

ICML 2026spotlight

Automating formal proofs of combinatorial identities is challenging for LLM-based provers, as long-horizon proof planning is required and unconstrained search quickly explodes. Symbolic methods such as the Wilf--Zeilberger (WZ) method can achieve a mechanized proof of combinatorial identities by con…

Cited by 0SourceScholar
2026

Numina-Lean-Agent: An Open and General Agentic Reasoning System for Formal Mathematics

ICML 2026poster

Agentic systems have recently become the dominant paradigm for formal theorem proving, achieving strong performance by coordinating multiple models and tools. However, existing approaches often rely on task-specific pipelines and trained formal provers, limiting their flexibility and reproducibility…

Cited by 0SourceScholar
2026

Property-Driven Protein Inverse Folding with Multi-Objective Preference Alignment

ICLR 2026poster

Protein sequence design must balance designability, defined as the ability to recover a target backbone, with multiple, often competing, developability properties such as solubility, thermostability, and expression. Existing approaches address these properties through post hoc mutation, inference-ti…

Cited by 0SourceScholar
2026

TempoMaster: Efficient Long Video Generation via Next-Frame-Rate Prediction

CVPR 2026

We present TempoMaster, a novel framework that formulates long video generation as next-frame-rate prediction. Specifically, we first generate a low-frame-rate clip that serves as a coarse blueprint of the entire video sequence, and then progressively increase the frame rate to refine visual details

Cited by 0SourceScholar
2022

Motion Sensitive Contrastive Learning for Self-Supervised Video Representation

ECCV 2022poster

"Contrastive learning has shown great potential in video representation learning. However, existing approaches fail to sufficiently exploit short-term motion dynamics, which are crucial to various down-stream video understanding tasks. In this paper, we propose Motion Sensitive Contrastive Learning…

Cited by 20SourcePDFScholar
2021

End-to-End Human Object Interaction Detection With HOI Transformer

CVPR 2021poster

We propose HOI Transformer to tackle human object interaction (HOI) detection in an end-to-end manner. Current approaches either decouple HOI task into separated stages of object detection and interaction classification or introduce surrogate interaction problem. In contrast, our method, named HOI T…

Cited by 266PDFcodeScholar
2020

Detailed 2D-3D Joint Representation for Human-Object Interaction

CVPR 2020poster

Human-Object Interaction (HOI) detection lies at the core of action understanding. Besides 2D information such as human/object appearance and locations, 3D pose is also usually utilized in HOI learning since its view-independence. However, rough 3D body joints just carry sparse body information and…

Cited by 175PDFcodeScholar