2 citations · 2 across the 7 of their papers we have counts for
8 papers
PolyOCR-Venus: Unified OCR Foundation Models for Text-Centric Visual Intelligence
GuangJian Team, Kaili Huang, Yongshuo Zhang +22
Optical Character Recognition (OCR) is evolving from plain-text transcription toward general visual intelligence, requiring models to recognize, localize, and reason over textual i…
LongDocBench: Benchmarking TOC Hierarchy and Contextual Relationship Recovery in Long Documents
Yuefeng Zou, Yichen Lu, Jingxiao Yang +5
Parsing visual documents into machine-readable representations is fundamental to document intelligence. Existing benchmarks focus on page-level element recognition, reading order,…
AgenticDataBench: A Comprehensive Benchmark for Data Agents
Zhaoyan Sun, Shan Zhong, Daizhou Wen +10
Data science aims to derive actionable insights from heterogeneous raw data, unlocking the value of the massive amounts of data generated in modern society. Automating this process…
Every Step Counts: Step-Level Credit Assignment for Tool-Integrated Text-to-SQL
Yaxun Dai, Baolin Sun, Junying Wang +6
Tool-integrated Text-to-SQL parsing has emerged as a promising paradigm, framing SQL generation as a sequential decision-making process interleaved with tool execution. However, ex…
Fast NF4 Dequantization Kernels for Large Language Model Inference
Xiangbo Qi, Chaoyi Jiang, Murali Annavaram
Large language models (LLMs) have grown beyond the memory capacity of single GPU devices, necessitating quantization techniques for practical deployment. While NF4 (4-bit NormalFlo…
Agentar-Scale-SQL: Advancing Text-to-SQL through Orchestrated Test-Time Scaling
Pengfei Wang, Baolin Sun, Xuemei Dong +7
State-of-the-art (SOTA) Text-to-SQL methods still lag significantly behind human experts on challenging benchmarks like BIRD. Current approaches that explore test-time scaling lack…
Agentar-Fin-R1: Enhancing Financial Intelligence through Domain Expertise, Training Efficiency, and Advanced Reasoning
Yanjun Zheng, Xiyang Du, Longfei Liao +10
Large Language Models (LLMs) exhibit considerable promise in financial applications; however, prevailing models frequently demonstrate limitations when confronted with scenarios th…
Agentar-DeepFinance-100K: A Large-Scale Financial Dataset via Systematic Chain-of-Thought Synthesis Optimization
Xiaoke Zhao, Zhaowen Zhou, Lin Chen +12
Recent advancements in large language models (LLMs) have demonstrated remarkable general reasoning capabilities, holding significant potential for applications in the financial dom…