3 citations · 8 across the 64 of their papers we have counts for
37 papers · 1 filter
Self-Rewarded Multimodal Coherent Reasoning Across Diverse Visual Domains
Jesen Zhang, Ningyuan Liu, Kaitong Cai +5
Multimodal LLMs often produce fluent yet unreliable reasoning, exhibiting weak step-to-step coherence and insufficient visual grounding, largely because existing alignment approach…
CoAgent: Collaborative Planning and Consistency Agent for Coherent Video Generation
Qinglin Zeng, Kaitong Cai, Ruiqi Chen +2
Maintaining narrative coherence and visual consistency remains a central challenge in open-domain video generation. Existing text-to-video models often treat each shot independentl…
RevFFN: Memory-Efficient Full-Parameter Fine-Tuning of Mixture-of-Experts LLMs with Reversible Blocks
Ningyuan Liu, Jing Yang, Kaitong Cai +1
Full parameter fine tuning is a key technique for adapting large language models (LLMs) to downstream tasks, but it incurs substantial memory overhead due to the need to cache exte…
FlashVLM: Text-Guided Visual Token Selection for Large Multimodal Models
Kaitong Cai, Jusheng Zhang, Jing Yang +4
Large vision-language models (VLMs) typically process hundreds or thousands of visual tokens per image or video frame, incurring quadratic attention cost and substantial redundancy…
SirenPose: Dynamic Scene Reconstruction via Geometric Supervision
Kaitong Cai, Jensen Zhang, Jing Yang +1
We introduce SirenPose, a geometry-aware loss formulation that integrates the periodic activation properties of sinusoidal representation networks with keypoint-based geometric sup…
LLM-CAS: Dynamic Neuron Perturbation for Real-Time Hallucination Correction
Jensen Zhang, Ningyuan Liu, Yijia Fan +5
Large language models (LLMs) often generate hallucinated content that lacks factual or contextual grounding, limiting their reliability in critical applications. Existing approache…
PTTA: A Pure Text-to-Animation Framework for High-Quality Creation
Ruiqi Chen, Kaitong Cai, Yijia Fan +1
Traditional animation production involves complex pipelines and significant manual labor cost. While recent video generation models such as Sora, Kling, and CogVideoX achieve impre…
Reflective Confidence: Correcting Reasoning Flaws via Online Self-Correction
Qinglin Zeng, Jing Yang, Keze Wang
Large language models (LLMs) have achieved strong performance on complex reasoning tasks using techniques such as chain-of-thought and self-consistency. However, ensemble-based app…
GTMA: Dynamic Representation Optimization for OOD Vision-Language Models
Jensen Zhang, Ningyuan Liu, Keze Wang
Vision-language models (VLMs) struggle in open-world applications, where out-of-distribution (OOD) concepts often trigger cross-modal alignment collapse and severely degrade zero-s…
Adaptive-VoCo: Complexity-Aware Visual Token Compression for Vision-Language Models
Xiaoyang Guo, Keze Wang
In recent years, large-scale vision-language models (VLMs) have demonstrated remarkable performance on multimodal understanding and reasoning tasks. However, handling high-dimensio…
Large Language Models as Discounted Bayesian Filters
Jensen Zhang, Jing Yang, Keze Wang
Large Language Models (LLMs) demonstrate strong few-shot generalization through in-context learning, yet their reasoning in dynamic and stochastic environments remains opaque. Prio…
STORM: Search-Guided Generative World Models for Robotic Manipulation
Wenjun Lin, Jensen Zhang, Kaitong Cai +1
We present STORM (Search-Guided Generative World Models), a novel framework for spatio-temporal reasoning in robotic manipulation that unifies diffusion-based action generation, co…
MM-CoT:A Benchmark for Probing Visual Chain-of-Thought Reasoning in Multimodal Models
Jusheng Zhang, Kaitong Cai, Xiaoyang Guo +10
The ability to perform Chain-of-Thought (CoT) reasoning marks a major milestone for multimodal models (MMs), enabling them to solve complex visual reasoning problems. Yet a critica…
Hybrid Token Compression for Vision-Language Models
Jusheng Zhang, Xiaoyang Guo, Tongyu Mo +5
Vision-language models (VLMs) rely on hundreds of visual tokens, leading to high computational and memory costs. Existing compression methods face a trade-off: continuous compressi…
PhyDetEx: Detecting and Explaining the Physical Plausibility of T2V Models
Zeqing Wang, Keze Wang, Lei Zhang
Driven by the growing capacity and training scale, Text-to-Video (T2V) generation models have recently achieved substantial progress in video quality, length, and instruction-follo…
Causal Invariance and Counterfactual Learning Driven Cooperative Game for Multi-Label Classification
Yijia Fan, Jusheng Zhang, Kaitong Cai +2
Multi-label classification (MLC) remains vulnerable to label imbalance, spurious correlations, and distribution shifts, challenges that are particularly detrimental to rare label p…
3DAlign-DAER: Dynamic Attention Policy and Efficient Retrieval Strategy for Fine-grained 3D-Text Alignment at Scale
Yijia Fan, Jusheng Zhang, Kaitong Cai +3
Despite recent advancements in 3D-text cross-modal alignment, existing state-of-the-art methods still struggle to align fine-grained textual semantics with detailed geometric struc…
Cost-Effective Communication: An Auction-based Method for Language Agent Interaction
Yijia Fan, Jusheng Zhang, Kaitong Cai +4
Multi-agent systems (MAS) built on large language models (LLMs) often suffer from inefficient "free-for-all" communication, leading to exponential token costs and low signal-to-noi…
MM-OPERA: Benchmarking Open-ended Association Reasoning for Large Vision-Language Models
Zimeng Huang, Jinxin Ke, Xiaoxuan Fan +9
Large Vision-Language Models (LVLMs) have exhibited remarkable progress. However, deficiencies remain compared to human intelligence, such as hallucination and shallow pattern matc…
Guardian: Decoupling Exploration from Safety in Reinforcement Learning
Kaitong Cai, Jusheng Zhang, Jing Yang +1
Hybrid offline--online reinforcement learning (O2O RL) promises both sample efficiency and robust exploration, but suffers from instability due to distribution shift between offlin…
RaCoT: Plug-and-Play Contrastive Example Generation Mechanism for Enhanced LLM Reasoning Reliability
Kaitong Cai, Jusheng Zhang, Yijia Fan +2
Retrieval-Augmented Generation (RAG) faces a core bottleneck with knowledge-sparse and semantically ambiguous long-tail queries, where retrieval noise distorts reasoning and necess…
Agent-GSPO: Communication-Efficient Multi-Agent Systems via Group Sequence Policy Optimization
Yijia Fan, Jusheng Zhang, Jing Yang +1
To combat the prohibitive communication costs of ``free-for-all" multi-agent systems (MAS), we introduce \textbf{Agent-GSPO}, a framework that directly optimizes for token economy…
Backward-Friendly Optimization: Training Large Language Models with Approximate Gradients under Memory Constraints
Jing Yang, Kaitong Cai, Yijia Fan +2
Full fine-tuning of Large Language Models (LLMs) is notoriously memory-intensive, primarily because conventional optimizers such as SGD or Adam assume access to exact gradients der…
Learning Dynamics of VLM Finetuning
Jusheng Zhang, Kaitong Cai, Jing Yang +1
Preference-based finetuning of vision--language models (VLMs) is brittle: trivially wrong negatives inject uninformative gradients that destabilize training. We recast alignment as…