CogGen uses a cognitively inspired recursive architecture with AVR for multimodal content to generate deep research reports that achieve SOTA among open-source systems and surpass Gemini Deep Research on a new OWID benchmark.
Arcs: Agentic retrieval-augmented code synthesis with iterative refinement
3 Pith papers cite this work. Polarity classification is still indexing.
years
2026 3verdicts
UNVERDICTED 3representative citing papers
MoCA-Agent decomposes questions into typed atomic claims, clears them via trader-agent markets into confidence-weighted decisions, synthesizes and verifies executable Python code, and reports strong benchmark scores including 78.3% on FinQA.
A survey of methods, benchmarks, and open challenges for large language models in multilingual code generation and translation.
citing papers explorer
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CogGen: A Cognitively Inspired Recursive Framework for Deep Research Report Generation
CogGen uses a cognitively inspired recursive architecture with AVR for multimodal content to generate deep research reports that achieve SOTA among open-source systems and surpass Gemini Deep Research on a new OWID benchmark.
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MoCA-Agent: A Market-of-Claims Code Agent for Financial and Numerical Reasoning
MoCA-Agent decomposes questions into typed atomic claims, clears them via trader-agent markets into confidence-weighted decisions, synthesizes and verifies executable Python code, and reports strong benchmark scores including 78.3% on FinQA.
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Large Language Models for Multilingual Code Intelligence: A Survey
A survey of methods, benchmarks, and open challenges for large language models in multilingual code generation and translation.