activity
20242026
collaborators

11 papers

cond-mat.mtrl-sci2026

Nonadiabatic polaron dynamics from machine-learned hopping trajectories

Daniela Mangano, Luca Leoni, Zhongfei Xu +2

The formation and motion of small polarons are ubiquitous in energy materials and influence photoinduced processes. Polaron transport is governed by thermally activated lattice dyn…

cs.CL2026

Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent

Lei Bai, Zongsheng Cao, Yang Chen +50

We introduce Agents-A1, a 35B Mixture-of-Experts Agentic Model that reaches trillion-parameter-level performance by scaling the agent horizon. We investigate agent-horizon scaling…

cs.CV2026

See What I Mean: Aligning Vision and Language Representations for Video Fine-grained Object Understanding

Boyuan Sun, Bowen Yin, Yuanming Li +2

We present SWIM (See What I Mean), a novel training strategy that aligns vision and language representations to enable fine-grained object understanding solely from textual prompts…

cs.AI2026

GeoAgent: Learning to Geolocate Everywhere with Reinforced Geographic Characteristics

Modi Jin, Yiming Zhang, Boyuan Sun +3

This paper presents GeoAgent, a model capable of reasoning closely with humans and deriving fine-grained address conclusions. Previous RL-based methods have achieved breakthroughs…

cs.CV2025

Depth Anything at Any Condition

Boyuan Sun, Modi Jin, Bowen Yin +1

We present Depth Anything at Any Condition (DepthAnything-AC), a foundation monocular depth estimation (MDE) model capable of handling diverse environmental conditions. Previous fo…

cs.CV2025

LLaVA-Scissor: Token Compression with Semantic Connected Components for Video LLMs

Boyuan Sun, Jiaxing Zhao, Xihan Wei +1

In this paper, we present LLaVA-Scissor, a training-free token compression strategy designed for video multimodal large language models. Previous methods mostly attempt to compress…

cs.CV2025

HumanOmniV2: From Understanding to Omni-Modal Reasoning with Context

Qize Yang, Shimin Yao, Weixuan Chen +7

With the rapid evolution of multimodal large language models, the capacity to deeply understand and interpret human intentions has emerged as a critical capability, which demands d…

cs.CV2025

HumanOmni: A Large Vision-Speech Language Model for Human-Centric Video Understanding

Jiaxing Zhao, Qize Yang, Yixing Peng +8

In human-centric scenes, the ability to simultaneously understand visual and auditory information is crucial. While recent omni models can process multiple modalities, they general…

cs.CV2025

Facial Dynamics in Video: Instruction Tuning for Improved Facial Expression Perception and Contextual Awareness

Jiaxing Zhao, Boyuan Sun, Xiang Chen +1

Facial expression captioning has found widespread application across various domains. Recently, the emergence of video Multimodal Large Language Models (MLLMs) has shown promise in…

cs.CV2025

LLaVA-Octopus: Unlocking Instruction-Driven Adaptive Projector Fusion for Video Understanding

Boyuan Sun, Jiaxing Zhao, Xiang Chen +2

In this paper, we introduce LLaVA-Octopus, a novel video multimodal large language model. LLaVA-Octopus adaptively weights features from different visual projectors based on user i…

cs.CV2024

Towards RAW Object Detection in Diverse Conditions

Zhong-Yu Li, Xin Jin, Boyuan Sun +2

Existing object detection methods often consider sRGB input, which was compressed from RAW data using ISP originally designed for visualization. However, such compression might los…