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20232026
most citedTool Learning with Large Language Models: A Survey

86 citations · 131 across the 55 of their papers we have counts for

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9 papers · 1 filter

cs.AI2026

DocOps: A Verifiable Benchmark for Autonomous Agents in Complex Document Operations

Jiazhen Jiang, Boxi Cao, Lingyong Yan +6

As autonomous agents rapidly evolve, their ability to reliably manipulate ubiquitous digital documents has become critical for enabling general-purpose AI assistants and automating…

cs.CV2026

How to Utilize Complementary Vision-Text Information for 2D Structure Understanding

Jiancheng Dong, Pengyue Jia, Derong Xu +9

LLMs typically linearize 2D tables into 1D sequences to fit their autoregressive architecture, which weakens row-column adjacency and other layout cues. In contrast, purely visual…

cs.AI2026

AdaFuse: Accelerating Dynamic Adapter Inference via Token-Level Pre-Gating and Fused Kernel Optimization

Qiyang Li, Rui Kong, Yuchen Li +5

The integration of dynamic, sparse structures like Mixture-of-Experts (MoE) with parameter-efficient adapters (e.g., LoRA) is a powerful technique for enhancing Large Language Mode…

cs.AI2026

Not All Preferences Deserve Gradients: Understanding Gradient Utility in Offline Reasoning Alignment

Hui Wu, Hengyi Cai, Jinman Zhao +6

Offline preference optimization aligns reasoning models from fixed chosen--rejected pairs, yet standard methods apply gradient updates from every pair regardless of its training va…

cs.CL2026

MatchTIR: Fine-Grained Supervision for Tool-Integrated Reasoning via Bipartite Matching

Changle Qu, Sunhao Dai, Hengyi Cai +3

Tool-Integrated Reasoning (TIR) empowers large language models (LLMs) to tackle complex tasks by interleaving reasoning steps with external tool interactions. However, existing rei…

cs.AI2026

Adversarial Yet Cooperative: Multi-Perspective Reasoning in Retrieved-Augmented Language Models

Can Xu, Lingyong Yan, Jiayi Wu +6

Recent advances in synergizing large reasoning models (LRMs) with retrieval-augmented generation (RAG) have shown promising results, yet two critical challenges remain: (1) reasoni…

cs.AI2026

Beyond Monolithic Architectures: A Multi-Agent Search and Knowledge Optimization Framework for Agentic Search

Yiqun Chen, Lingyong Yan, Zixuan Yang +5

Agentic search has emerged as a promising paradigm for complex information seeking by enabling Large Language Models (LLMs) to interleave reasoning with tool use. However, prevaili…

cs.DC2026

FlexSpec: Frozen Drafts Meet Evolving Targets in Edge-Cloud Collaborative LLM Speculative Decoding

Yuchen Li, Rui Kong, Zhonghao Lyu +11

Deploying large language models (LLMs) in mobile and edge computing environments is constrained by limited on-device resources, scarce wireless bandwidth, and frequent model evolut…

cs.AI2026

Reinforced Efficient Reasoning via Semantically Diverse Exploration

Ziqi Zhao, Zhaochun Ren, Jiahong Zou +9

Reinforcement learning with verifiable rewards (RLVR) has proven effective in enhancing the reasoning of large language models (LLMs). Monte Carlo Tree Search (MCTS)-based extensio…