13 citations · 26 across the 41 of their papers we have counts for
10 papers · 1 filter
Simulation-Free Hierarchical Latent Policy Planning for Proactive Dialogues
Tao He, Lizi Liao, Yixin Cao +5
Recent advancements in proactive dialogues have garnered significant attention, particularly for more complex objectives (e.g. emotion support and persuasion). Unlike traditional t…
From Specific-MLLMs to Omni-MLLMs: A Survey on MLLMs Aligned with Multi-modalities
Shixin Jiang, Jiafeng Liang, Jiyuan Wang +6
To tackle complex tasks in real-world scenarios, more researchers are focusing on Omni-MLLMs, which aim to achieve omni-modal understanding and generation. Beyond the constraints o…
CFSP: An Efficient Structured Pruning Framework for LLMs with Coarse-to-Fine Activation Information
Yuxin Wang, Minghua Ma, Zekun Wang +7
The colossal parameters and computational overhead of Large Language Models (LLMs) challenge their real-world applications. Network pruning, which targets unstructured or structure…
GraCoRe: Benchmarking Graph Comprehension and Complex Reasoning in Large Language Models
Zike Yuan, Ming Liu, Hui Wang +1
Evaluating the graph comprehension and reasoning abilities of Large Language Models (LLMs) is challenging and often incomplete. Existing benchmarks focus primarily on pure graph un…
BeamAggR: Beam Aggregation Reasoning over Multi-source Knowledge for Multi-hop Question Answering
Zheng Chu, Jingchang Chen, Qianglong Chen +6
Large language models (LLMs) have demonstrated strong reasoning capabilities. Nevertheless, they still suffer from factual errors when tackling knowledge-intensive tasks. Retrieval…
GUIDE: A Guideline-Guided Dataset for Instructional Video Comprehension
Jiafeng Liang, Shixin Jiang, Zekun Wang +7
There are substantial instructional videos on the Internet, which provide us tutorials for completing various tasks. Existing instructional video datasets only focus on specific st…
Planning Like Human: A Dual-process Framework for Dialogue Planning
Tao He, Lizi Liao, Yixin Cao +4
In proactive dialogue, the challenge lies not just in generating responses but in steering conversations toward predetermined goals, a task where Large Language Models (LLMs) typic…
Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation
Jingchang Chen, Hongxuan Tang, Zheng Chu +4
Despite recent progress made by large language models in code generation, they still struggle with programs that meet complex requirements. Recent work utilizes plan-and-solve deco…
KwaiAgents: Generalized Information-seeking Agent System with Large Language Models
Haojie Pan, Zepeng Zhai, Hao Yuan +5
Driven by curiosity, humans have continually sought to explore and understand the world around them, leading to the invention of various tools to satiate this inquisitiveness. Desp…
CogGPT: Unleashing the Power of Cognitive Dynamics on Large Language Models
Yaojia Lv, Haojie Pan, Zekun Wang +6
Cognitive dynamics are pivotal to advance human understanding of the world. Recent advancements in large language models (LLMs) reveal their potential for cognitive simulation. How…