Papers12

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#synthetic data generation

UltraDexGrasp: Learning Universal Dexterous Grasping for Bimanual Robots with Synthetic Data

Intermediate

Sizhe Yang, Yiman Xie et al.Mar 5arXiv

Robots need many different ways to grab things, just like people use pinch, tripod, whole-hand, or two hands together.

#bimanual dexterous grasping#universal grasp policy#synthetic data generation

KARL: Knowledge Agents via Reinforcement Learning

Beginner

Jonathan D. Chang, Andrew Drozdov et al.Mar 5arXiv

KARL is a smart search helper that learns to look up information step by step and explain answers using the facts it finds.

#grounded reasoning#enterprise search#reinforcement learning

FireRed-OCR Technical Report

Intermediate

Hao Wu, Haoran Lou et al.Mar 2arXiv

FireRed-OCR turns a general vision-language model into a careful document reader that follows strict rules, so its outputs are usable in the real world.

#FireRed-OCR#structural hallucination#document parsing

CHIMERA: Compact Synthetic Data for Generalizable LLM Reasoning

Beginner

Xinyu Zhu, Yihao Feng et al.Mar 1arXiv

CHIMERA is a small (about 9,000 examples) but very carefully built synthetic dataset that teaches AI to solve hard problems step by step.

#CHIMERA dataset#synthetic data generation#chain-of-thought

Tool-R0: Self-Evolving LLM Agents for Tool-Learning from Zero Data

Beginner

Emre Can Acikgoz, Cheng Qian et al.Feb 24arXiv

Tool-R0 teaches a language model to use software tools (like APIs) with zero human-made training data.

#self-play reinforcement learning#tool calling#function calling

ExStrucTiny: A Benchmark for Schema-Variable Structured Information Extraction from Document Images

Intermediate

Mathieu Sibue, Andres Muñoz Garza et al.Feb 12arXiv

ExStrucTiny is a new test (benchmark) that checks if AI can pull many connected facts from all kinds of documents and neatly put them into JSON, even when the question style and schema change.

#structured information extraction#document understanding#vision-language models

User-Oriented Multi-Turn Dialogue Generation with Tool Use at scale

Intermediate

Jungho Cho, Minbyul Jeong et al.Jan 13arXiv

The paper builds a new way to create realistic, long conversations between people and AI that use tools like databases.

#multi-turn dialogue generation#tool use#user simulation

Solar Open Technical Report

Intermediate

Sungrae Park, Sanghoon Kim et al.Jan 11arXiv

Solar Open is a giant bilingual AI (102 billion parameters) that focuses on helping underserved languages like Korean catch up with English-level AI quality.

#Solar Open#Mixture-of-Experts#bilingual LLM

X-Coder: Advancing Competitive Programming with Fully Synthetic Tasks, Solutions, and Tests

Intermediate

Jie Wu, Haoling Li et al.Jan 11arXiv

X-Coder shows that models can learn expert-level competitive programming using data that is 100% synthetic—no real contest problems needed.

#competitive programming#synthetic data generation#feature-based synthesis

DataFlow: An LLM-Driven Framework for Unified Data Preparation and Workflow Automation in the Era of Data-Centric AI

Intermediate

Hao Liang, Xiaochen Ma et al.Dec 18arXiv

DataFlow is a building-block system that helps large language models get better data by unifying how we create, clean, check, and organize that data.

#DataFlow#LLM data preparation#operator pipeline

VOYAGER: A Training Free Approach for Generating Diverse Datasets using LLMs

Intermediate

Avinash Amballa, Yashas Malur Saidutta et al.Dec 12arXiv

VOYAGER is a training-free way to make large language models (LLMs) create data that is truly different, not just slightly reworded.

#VOYAGER#determinantal point process#dataset diversity

M3DR: Towards Universal Multilingual Multimodal Document Retrieval

Intermediate

Adithya S Kolavi, Vyoman JainDec 3arXiv

The paper introduces M3DR, a way for computers to find the right document image no matter which of 22 languages the query or the document uses.

#multilingual retrieval#multimodal retrieval#document image search