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20232026
most citedVideo Understanding with Large Language Models: A Survey

8 citations · 18 across the 20 of their papers we have counts for

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5 papers · 1 filter

cs.CL2026

Many Steps into One: Reasoning Contraction and the Limits of Safe Memory Reuse for LLM Agents

Jianghong Zhou, Hao Rong, Chen Lin +1

Thought templates, skill libraries, agent memories and caches turn many reasoning steps into one. We call this reasoning contraction. A contracted memory saves reasoning steps and…

cs.CL2026

Beyond Oracle Communication: Benchmarking Interactive Intent Alignment Under Miscommunication and Evolving User Intent

Zheyuan Zhang, Mengyuan Chao, Ke Xiao +5

Modern LLM agents increasingly tackle complex tasks through interactive, long-horizon exchanges with users, while existing benchmarks generally assume that users always accurately…

cs.CL2025

Why Reasoning Matters? A Survey of Advancements in Multimodal Reasoning (v1)

Jing Bi, Susan Liang, Xiaofei Zhou +16

Reasoning is central to human intelligence, enabling structured problem-solving across diverse tasks. Recent advances in large language models (LLMs) have greatly enhanced their re…

cs.CL2025

Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMs

Dayu Yang, Tianyang Liu, Daoan Zhang +8

In large language models (LLMs), code and reasoning reinforce each other: code offers an abstract, modular, and logic-driven structure that supports reasoning, while reasoning tran…

cs.CL2024

DeFine: Decision-Making with Analogical Reasoning over Factor Profiles

Yebowen Hu, Xiaoyang Wang, Wenlin Yao +5

LLMs are ideal for decision-making thanks to their ability to reason over long contexts. However, challenges arise when processing speech transcripts that describe complex scenario…