activity
20232026
most citedLMME3DHF: Benchmarking and Evaluating Multimodal 3D Human Face Generation with LMMs

7 citations · 26 across the 31 of their papers we have counts for

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9 papers · 1 filter

cs.LG2026

Intern-S2-Preview: Scientific Agentic Foundation Model

Lei Bai, Jiaqi Cao, Chiyu Chen +121

Scientific discovery increasingly requires AI systems that can reason over scientific evidence of heterogeneous modalities, interact with scientific tools and environments, and sus…

cs.AI2026

TREND-10K: A Comprehensive Dataset for Next-Generation Video Quality Assessment Based on Preference-Driven Media

Ziheng Jia, Zicheng Zhang, Junqi Zhang +4

The increasing prominence of short-video platforms, coupled with the advanced commercialization of AI-generated content (AIGC) videos, has led to a shift in the types of video medi…

cs.CV2026

Emo-Bench: A Scalable Benchmark for Multimodal Evoked and Expressed Emotion Understanding via Bayesian Pairwise Alignment

Lancheng Gao, Ziheng Jia, Shengyan Li +4

Understanding both expressed and evoked emotions is critical for multimodal large language models (MLLMs) to achieve comprehensive affect-aware interactions. However, existing benc…

cs.CV2026

3DGSI-Assessor: A Large-Scale Dataset and An LMM-based Method for 3D Gaussian Splatting Image Quality Assessment

Yuke Xing, Jiarui Wang, William Gordon +3

3D Gaussian Splatting (3DGS) has become a dominant representation for real-time novel view synthesis (NVS), yet its storage footprint makes compression indispensable for practical…

cs.CL2026

Memory Decoder at Scale: A Pretrained, Parametric Long-Term Memory

Rubin Wei, Jiaqi Cao, Jiarui Wang +4

Decoder-only language models entangle long-term memory and reasoning in a single parameter set, making it difficult to scale memory capacity independently. Memory Decoder introduce…

cs.LG2026

MemSFT: Mitigating Alignment Tax with an External Parametric Memory

Jiarui Wang, Xiang Shi, Jiaqi Cao +8

Adapting Large Language Models (LLMs) to specialized domains often incurs an alignment tax, as fine-tuning on domain-specific tasks can cause catastrophic forgetting and substantia…

cs.CV2026

DynT2I-Eval: A Dynamic Evaluation Framework for Text-to-Image Models

Juntong Wang, Jiarui Wang, Huiyu Duan +3

Existing text-to-image (T2I) benchmarks largely rely on fixed prompt sets, leaving them vulnerable to overfitting and benchmark contamination once publicly released and repeatedly…

cs.IR2026

Beyond Item IDs: Scaling Short-Form-Video Recommendation via Semantic-Native Long Sequence Modeling

Ruixiao Sun, Diego Uribe Mora, Zhimeng Jiang +7

Capturing user interests across extensive watch histories is critical for short-form video recommendation, yet scaling sequence length is limited by two bottlenecks: the semantic s…

cs.DC2026

RelayGR: Scaling Long-Sequence Generative Recommendation via Cross-Stage Relay-Race Inference

Jiarui Wang, Huichao Chai, Yuanhang Zhang +38

Real-time recommender systems execute multi-stage cascades (retrieval, pre-processing, fine-grained ranking) under strict tail-latency SLOs, leaving only tens of milliseconds for r…