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cs.CL2025

WebAggregator: Enhancing Compositional Reasoning Capabilities of Deep Research Agent Foundation Models

Rui Wang, Ce Zhang, Jun-Yu Ma +10

The hallmark of Deep Research agents lies in compositional reasoning, the capacity to aggregate distributed, heterogeneous information into coherent logical insights. However, curr…

cs.CL2025

UniGist: Towards General and Hardware-aligned Sequence-level Long Context Compression

Chenlong Deng, Zhisong Zhang, Kelong Mao +6

Large language models are increasingly capable of handling long-context inputs, but the memory overhead of key-value (KV) cache remains a major bottleneck for general-purpose deplo…

cs.AI2025

Cognitive Kernel-Pro: A Framework for Deep Research Agents and Agent Foundation Models Training

Tianqing Fang, Zhisong Zhang, Xiaoyang Wang +16

General AI Agents are increasingly recognized as foundational frameworks for the next generation of artificial intelligence, enabling complex reasoning, web interaction, coding, an…

cs.CL2025

Recall with Reasoning: Chain-of-Thought Distillation for Mamba's Long-Context Memory and Extrapolation

Junyu Ma, Tianqing Fang, Zhisong Zhang +3

Mamba's theoretical infinite-context potential is limited in practice when sequences far exceed training lengths. This work explores unlocking Mamba's long-context memory ability b…

cs.CV2025

VScan: Rethinking Visual Token Reduction for Efficient Large Vision-Language Models

Ce Zhang, Kaixin Ma, Tianqing Fang +5

Recent Large Vision-Language Models (LVLMs) have advanced multi-modal understanding by incorporating finer-grained visual perception and encoding. However, such methods incur signi…

cs.CL2025

InComeS: Integrating Compression and Selection Mechanisms into LLMs for Efficient Model Editing

Shuaiyi Li, Zhisong Zhang, Yang Deng +6

Although existing model editing methods perform well in recalling exact edit facts, they often struggle in complex scenarios that require deeper semantic understanding rather than…