14 citations · 17 across the 12 of their papers we have counts for
12 papers
MuseCritic: Learning Multi-Aspect Song Rewards through Natural-Language Aesthetic Critiques
Jiabao Zhuang, Changhao Jiang, Hanchen Wang +11
Long-form song generation models continue to improve in duration, structural coherence, and acoustic complexity, increasing the need for reliable aesthetic rewards aligned with hum…
TIER-MoE: Trust-Informed Expert Routing via Conditional Modality Risk for Multimodal Fusion in Biomedical Classification
Yu Chang, Anzhe Cheng, Chenwei Wu +7
The promise of multimodal fusion lies in combining complementary sources of evidence, yet more evidence does not always yield a better prediction. Recent multimodal models have adv…
ProphetKV: User-Query-Driven Selective Recomputation for Efficient KV Cache Reuse in Retrieval-Augmented Generation
Shihao Wang, Jiahao Chen, Yanqi Pan +7
The prefill stage of long-context Retrieval-Augmented Generation (RAG) is severely bottlenecked by computational overhead. To mitigate this, recent methods assemble pre-calculated…
Kimi K2.5: Visual Agentic Intelligence
Kimi Team, Tongtong Bai, Yifan Bai +333
We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that…
Attributing and Exploiting Safety Vectors through Global Optimization in Large Language Models
Fengheng Chu, Jiahao Chen, Yuhong Wang +4
While Large Language Models (LLMs) are aligned to mitigate risks, their safety guardrails remain fragile against jailbreak attacks. This reveals limited understanding of components…
Muse: Towards Reproducible Long-Form Song Generation with Fine-Grained Style Control
Changhao Jiang, Jiahao Chen, Zhenghao Xiang +14
Recent commercial systems such as Suno demonstrate strong capabilities in long-form song generation, while academic research remains largely non-reproducible due to the lack of pub…
Private Map-Secure Reduce: Infrastructure for Efficient AI Data Markets
Sameer Wagh, Kenneth Stibler, Shubham Gupta +8
The modern AI data economy centralizes power, limits innovation, and misallocates value by extracting data without control, privacy, or fair compensation. We introduce Private Map-…
MaskAttn-SDXL: Controllable Region-Level Text-To-Image Generation
Yu Chang, Jiahao Chen, Anzhe Cheng +1
Diffusion models have achieved strong results in text-to-image generation, but important limitations remain as prompts become more structured and multi-object. On the architecture…
QTMRL: An Agent for Quantitative Trading Decision-Making Based on Multi-Indicator Guided Reinforcement Learning
Jingfeng Pan, Jiahao Chen
In the highly volatile and uncertain global financial markets, traditional quantitative trading models relying on statistical modeling or empirical rules often fail to adapt to dyn…
Kimi K2: Open Agentic Intelligence
Kimi Team, Yifan Bai, Yiping Bao +195
We introduce Kimi K2, a Mixture-of-Experts (MoE) large language model with 32 billion activated parameters and 1 trillion total parameters. We propose the MuonClip optimizer, which…
The Singapore Consensus on Global AI Safety Research Priorities
Yoshua Bengio, Tegan Maharaj, Luke Ong +84
Rapidly improving AI capabilities and autonomy hold significant promise of transformation, but are also driving vigorous debate on how to ensure that AI is safe, i.e., trustworthy,…
The Right Way to Search Evolving Graphs
Jiahao Chen, Weijian Zhang
Evolving graphs arise in problems where interrelations between data change over time. We present a breadth first search (BFS) algorithm for evolving graphs that computes the most d…