Copertina

Scaling Agentic Capabilities via Grounded Interaction Synthesis

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Shi, Wenhang, Dong, Jinhao, Chen, Yiren, Zhao, Zhe, Bian, Shuqing, Lu, Wei, Du, Xiaoyong
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Training Prompt Matters: State-Adaptive Optimization for Robust Fine-Tuning
di: Shi, Wenhang, et al.
Pubblicazione: (2026)

Investigating the Impact of Rationales for LLMs on Natural Language Understanding
di: Shi, Wenhang, et al.
Pubblicazione: (2025)

Joint Knowledge Editing for Information Enrichment and Probability Promotion
di: Shi, Wenhang, et al.
Pubblicazione: (2024)

No Loss, No Gain: Gated Refinement and Adaptive Compression for Prompt Optimization
di: Shi, Wenhang, et al.
Pubblicazione: (2025)

LLM-Optic: Unveiling the Capabilities of Large Language Models for Universal Visual Grounding
di: Zhao, Haoyu, et al.
Pubblicazione: (2024)

Arch: An AI-Native Hardware Description Language for Register-Transfer Clocked Hardware Design
di: Zhao, Shuqing
Pubblicazione: (2026)

Team of Thoughts: Efficient Test-time Scaling of Agentic Systems through Orchestrated Tool Calling
di: Wong, Jeffrey T. H., et al.
Pubblicazione: (2026)

CAFE: Retrieval Head-based Coarse-to-Fine Information Seeking to Enhance Multi-Document QA Capability
di: Peng, Han, et al.
Pubblicazione: (2025)

DeepAnalyze: Agentic Large Language Models for Autonomous Data Science
di: Zhang, Shaolei, et al.
Pubblicazione: (2025)

RadFabric: Agentic AI System with Reasoning Capability for Radiology
di: Chen, Wenting, et al.
Pubblicazione: (2025)

AsyncSpade: Efficient Test-Time Scaling with Asynchronous Sparse Decoding
di: Luo, Shuqing, et al.
Pubblicazione: (2025)

R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
di: Song, Huatong, et al.
Pubblicazione: (2025)

DeepDistill: Enhancing LLM Reasoning Capabilities via Large-Scale Difficulty-Graded Data Training
di: Tian, Xiaoyu, et al.
Pubblicazione: (2025)

A-RAG: Scaling Agentic Retrieval-Augmented Generation via Hierarchical Retrieval Interfaces
di: Du, Mingxuan, et al.
Pubblicazione: (2026)

Agentic Aggregation for Parallel Scaling of Long-Horizon Agentic Tasks
di: Lee, Yoonsang, et al.
Pubblicazione: (2026)

SuperValid: Capability-Aligned OOD Validation for Generalizable Downstream Scaling
di: Sun, Quanen, et al.
Pubblicazione: (2026)

Scaling Computer-Use Grounding via User Interface Decomposition and Synthesis
di: Xie, Tianbao, et al.
Pubblicazione: (2025)

RAGCap-Bench: Benchmarking Capabilities of LLMs in Agentic Retrieval Augmented Generation Systems
di: Lin, Jingru, et al.
Pubblicazione: (2025)

Scaling Laws For Mixed Quantization
di: Cao, Zeyu, et al.
Pubblicazione: (2024)

Towards General Agentic Intelligence via Environment Scaling
di: Fang, Runnan, et al.
Pubblicazione: (2025)

On Data Engineering for Scaling LLM Terminal Capabilities
di: Pi, Renjie, et al.
Pubblicazione: (2026)

ASTER: Agentic Scaling with Tool-integrated Extended Reasoning
di: Zhang, Xuqin, et al.
Pubblicazione: (2026)

ConflictBench: Evaluating Human-AI Conflict via Interactive and Visually Grounded Environments
di: Zhao, Weixiang, et al.
Pubblicazione: (2026)

Scaling Agentic Verifier for Competitive Coding
di: Ma, Zeyao, et al.
Pubblicazione: (2026)

MaskSearch: A Universal Pre-Training Framework to Enhance Agentic Search Capability
di: Wu, Weiqi, et al.
Pubblicazione: (2025)

Unleashing LLM Reasoning Capability via Scalable Question Synthesis from Scratch
di: Ding, Yuyang, et al.
Pubblicazione: (2024)

EnvScaler: Scaling Tool-Interactive Environments for LLM Agent via Programmatic Synthesis
di: Song, Xiaoshuai, et al.
Pubblicazione: (2026)

KnowCoder-A1: Incentivizing Agentic Reasoning Capability with Outcome Supervision for KBQA
di: Chen, Zhuo, et al.
Pubblicazione: (2025)

Nexus: Execution-Grounded Multi-Agent Test Oracle Synthesis
di: Huang, Dong, et al.
Pubblicazione: (2025)

GameDevBench: Evaluating Agentic Capabilities Through Game Development
di: Chi, Wayne, et al.
Pubblicazione: (2026)

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law
di: Ge, Qiming, et al.
Pubblicazione: (2025)

UI-E2I-Synth: Advancing GUI Grounding with Large-Scale Instruction Synthesis
di: Liu, Xinyi, et al.
Pubblicazione: (2025)

A Two-Phase Recall-and-Select Framework for Fast Model Selection
di: Cui, Jianwei, et al.
Pubblicazione: (2024)

MOAT: Evaluating LMMs for Capability Integration and Instruction Grounding
di: Ye, Zhoutong, et al.
Pubblicazione: (2025)

Beyond Pixels: Introspective and Interactive Grounding for Visualization Agents
di: Lu, Yiyang, et al.
Pubblicazione: (2026)

Efficient Machine Translation with a BiLSTM-Attention Approach
di: Wu, Yuxu, et al.
Pubblicazione: (2024)

Large Language Model for Table Processing: A Survey
di: Lu, Weizheng, et al.
Pubblicazione: (2024)

DocDancer: Towards Agentic Document-Grounded Information Seeking
di: Zhang, Qintong, et al.
Pubblicazione: (2026)

Towards Corpus-Grounded Agentic LLMs for Multilingual Grammatical Analysis
di: Klemen, Matej, et al.
Pubblicazione: (2025)

Evaluating Accounting Reasoning Capabilities of Large Language Models
di: Zhou, Jie, et al.
Pubblicazione: (2026)