6 citations · 18 across the 37 of their papers we have counts for
13 papers · 1 filter
Teaching Vision-Language Models to Use the Scale They Are Given: Label-Free Equivariance Training for Metric Physical Reasoning
Kaizhen Tan, Yang Feng, Heqing Du +3
Metric questions about video, such as the speed of a moving object, require a vision-language model to convert visual measurements into physical units using a real-world reference…
Sequential Trajectories and Simultaneous Blending: Multi-Emotion Modeling for Instruction-Following TTS
Yan Zhou, Yun Hong, Yang Feng
Natural-language instructions enable flexible control of synthesized speech, yet emotional TTS systems primarily model a single utterance-level affect, leaving multi-emotion contro…
Beyond Multimodal Alignment: Shared Physical Representations Across Sensors and Action Orders
Kaizhen Tan, Xin Xu, Siru Tao +4
Multimodal world models are often evaluated by whether different sensors produce similar representations. However, similar representations do not necessarily imply that the models…
What Can Latent World Models Know? Physical Information in Multimodal Predictive Representations
Kaizhen Tan, Sizhe Xu, Xin Xu +6
A central premise of latent world models is that predicting the future encourages representations to internalize the physics of their environment. We ask which physical quantities…
How Much Can a LoRA Adapter Memorize? Measuring Adapter Capacity in Bits
Kaizhen Tan, Heqing Du, Yang Feng
LoRA adapters are often shared on their own, and the amount of information they can hold about their training data bounds what sharing them can reveal. Following Morris et al. (202…
BayLing-Duplex: Native Full-Duplex Speech Dialogue with a Single Autoregressive LLM
Qingkai Fang, Shoutao Guo, Yang Feng
Real-time, full-duplex speech interaction is a key feature of next-generation spoken chatbots, allowing the model to listen and speak at the same time and to handle natural phenome…
FreezeEmpath: Efficient Training for Empathetic Spoken Chatbots with Frozen LLMs
Yun Hong, Yan Zhou, Yang Feng
Empathy is essential for fostering natural interactions in spoken dialogue systems, as it enables machines to recognize the emotional tone of human speech and deliver empathetic re…
Language on Demand, Knowledge at Core: Composing LLMs with Encoder-Decoder Translation Models for Extensible Multilinguality
Mengyu Bu, Yang Feng
Large language models (LLMs) exhibit strong general intelligence, yet their multilingual performance remains highly imbalanced. Although LLMs encode substantial cross-lingual knowl…
From Attenuation to Attention: Variational Information Flow Manipulation for Fine-Grained Visual Perception
Jilong Zhu, Yang Feng
While Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in general visual understanding, they frequently falter in fine-grained perception tasks th…
SpecBound: Adaptive Bounded Self-Speculation with Layer-wise Confidence Calibration
Zhuofan Wen, Yang Feng
Speculative decoding has emerged as a promising approach to accelerate autoregressive inference in large language models (LLMs). Self-draft methods, which leverage the base LLM its…
Efficient Training for Cross-lingual Speech Language Models
Yan Zhou, Qingkai Fang, Yun Hong +1
Currently, large language models (LLMs) predominantly focus on the text modality. To enable more natural human-AI interaction, speech LLMs are emerging, but building effective end-…
Confidence under Visual Token Pruning: Removed Evidence and Risk-Controlled Token Budgets for MLLMs
Kaizhen Tan, Yang Feng, Heqing Du +3
Visual token pruning speeds up multimodal large language models (MLLMs) by keeping a small subset of the visual tokens, and pruning methods are compared by the accuracy they retain…
CREG: Compass Relational Evidence Graph for Characterizing Directional Structure in VLM Spatial-Reasoning Attribution
Kaizhen Tan, Yang Feng, Heqing Du
Standard attribution heatmaps show where a vision-language model (VLM) focuses, but they do not reveal whether the recovered evidence is organized by the queried spatial relation o…