1.6k citations · 2.7k across the 28 of their papers we have counts for
13 papers · 1 filter
Probabilistic Multi-Source Data Selection via Learnable Categorical Priors: Variance Reduction and Guaranteed Derandomization
Shizhan Cai, Qixin Zhang, Siyuan Ma +3
Bilevel data selection is a fundamental task with numerous applications in machine learning and statistics. A common strategy for tackling this problem is to relax the original bil…
FutureBridge: Token Selection Beyond Local Preference in Collaborative Decoding
Quanquan Li, Hongbo Zhang, Yihe Chi +9
Token-level collaboration allows a large language model (LLM) to assist a small language model (SLM) when their predictions diverge. Existing methods either use LLM-generated inter…
Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures
SiYuan Ma, Yiqin Luo, Zhangji +8
Identical language-model answers can arise from hidden states that support different future computations, so current-answer probes do not establish a reusable internal interface. W…
Text as Partial Constraint: Core-Residual Alignment for Robust Vision-Language Learning
Chengzhen Yu, Canran Xiao, Siyuan Ma +1
Vision-language alignment powers open-vocabulary recognition, retrieval, and LVLM grounding, yet natural captions are often underspecified, making similarity brittle and overly con…
Attention-Spectrum Regularization for Replay-Free Continual Multimodal LLMs
Chuangxin Zhao, Canran Xiao, Siyuan Ma +5
Multimodal large language models (MLLMs) are increasingly required to adapt to non-stationary streams of visual domains, question types, and user instructions, yet continual fine-t…
Agent-Assisted Side-Channel Attacks on Non-Prefix KV Cache in RAG
He Sun, Shinan Liu, Siyuan Ma +3
Modern Large Language Model (LLM) serving engines increasingly rely on Retrieval-Augmented Generation (RAG) and non-prefix Key-Value (KV) cache fusion to accelerate long-context, m…
Large Language Models as Amortized Pareto-Front Generators for Constrained Bi-Objective Convex Optimization
Peipei Xu, SiYuan Ma, Yaohua Liu +4
Generating feasible Pareto fronts for constrained bi-objective continuous optimization is central to multi-criteria decision-making. Existing methods usually rely on iterative scal…
BOOKAGENT: Orchestrating Safety-Aware Visual Narratives via Multi-Agent Cognitive Calibration
Bo Gao, Chang Liu, Yuyang Miao +2
Recent advancements in Large Generative Models (LGMs) have revolutionized multi-modal generation. However, generating illustrated storybooks remains an open challenge, where prior…
A comparative study on power delivery aspects of compute-in/near-memory approaches using DRAM
Siddhartha Raman Sundara Raman, Siyuan Ma, Lizy Kurian John
Compute-in-memory (PIM) mitigates the memory wall by performing computation within memory, reducing data movement and improving energy efficiency. DRAM-based PIM is particularly at…
The Latent Space: Foundation, Evolution, Mechanism, Ability, and Outlook
Xinlei Yu, Zhangquan Chen, Yongbo He +36
Latent space is rapidly emerging as a native substrate for language-based models. While modern systems are still commonly understood through explicit token-level generation, an inc…
CoT2-Meta: Budgeted Metacognitive Control for Test-Time Reasoning
Siyuan Ma, Bo Gao, Zikai Xiao +6
Recent test-time reasoning methods improve performance by generating more candidate chains or searching over larger reasoning trees, but they typically lack explicit control over w…
MME-CoF-Pro: Evaluating Reasoning Coherence in Video Generative Models with Text and Visual Hints
Yu Qi, Xinyi Xu, Ziyu Guo +10
Video generative models show emerging reasoning behaviors. It is essential to ensure that generated events remain causally consistent across frames for reliable deployment, a prope…
ODAR: Principled Adaptive Routing for LLM Reasoning via Active Inference
Siyuan Ma, Bo Gao, Xiaojun Jia +6
The paradigm of large language model (LLM) reasoning is shifting from parameter scaling to test-time compute scaling, yet many existing approaches still rely on uniform brute-force…