9 papers
Convolution for Large Language Models
Yuchuan Tian, Yingte Shu, Wei He +7
Large language models (LLMs) largely rely on Transformers, where self-attention provides global token interaction but does not explicitly encode the locality of natural language. W…
StoicLLM: Preference Optimization for Philosophical Alignment in Small Language Models
Ishmam Khan, Sindhuja Thogarrati, Shuo Zhang
While large language models excel at factual adaptation, their ability to internalize nuanced philosophical frameworks under severe data constraints remains underexplored. We inves…
Improving Music Source Separation with Diffusion and Consistency Refinement
Tornike Karchkhadze, Mohammad Rasool Izadi, Shuo Zhang +1
In this work, we propose an approach to music source separation that uses a generative diffusion model as a last-stage refinement on top of a deterministic separator, progressively…
ACE-Router: Generalizing History-Aware Routing from MCP Tools to the Agent Web
Zhiyuan Yao, Zishan Xu, Yifu Guo +6
With the rise of the Agent Web and Model Context Protocol (MCP), the agent ecosystem is evolving into an open collaborative network, exponentially increasing accessible tools. Howe…
FloCA: Towards Faithful and Logically Consistent Flowchart Reasoning
Jinzi Zou, Bolin Wang, Liang Li +3
Flowchart-oriented dialogue (FOD) systems aim to guide users through multi-turn decision-making or operational procedures by following a domain-specific flowchart to achieve a task…
From Next-Token to Next-Block: A Principled Adaptation Path for Diffusion LLMs
Yuchuan Tian, Yuchen Liang, Shuo Zhang +10
Diffusion Language Models (DLMs) enable fast generation, yet training large DLMs from scratch is costly. As a practical shortcut, adapting off-the-shelf Auto-Regressive (AR) model…