Multimodal LLMs process code as images to achieve up to 8x token compression, with visual cues like syntax highlighting aiding tasks and clone detection remaining resilient or even improving under compression.
Reasoning in Trees: Improving Retrieval-Augmented Generation for Multi-Hop Question Answering,
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LLM reasoning is primarily mediated by latent-state trajectories rather than by explicit surface chain-of-thought outputs.
HDRR combines document-level semantic routing with scoped chunk retrieval to outperform both pure chunk-based retrieval and semantic file routing on the FinDER benchmark, delivering higher average scores, lower failure rates, and more perfect answers.
Sol2Vy transfers vulnerability detection from Solidity to Vyper in zero-shot fashion, outperforming prior methods on reentrancy, weak randomness, and unchecked transfers.
Neural reranking in a hybrid RAG system raises high-quality answer rates from 33.5% to 49.0% on financial report questions.
citing papers explorer
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CodeOCR: On the Effectiveness of Vision Language Models in Code Understanding
Multimodal LLMs process code as images to achieve up to 8x token compression, with visual cues like syntax highlighting aiding tasks and clone detection remaining resilient or even improving under compression.
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LLM Reasoning Is Latent, Not the Chain of Thought
LLM reasoning is primarily mediated by latent-state trajectories rather than by explicit surface chain-of-thought outputs.
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Resolving the Robustness-Precision Trade-off in Financial RAG through Hybrid Document-Routed Retrieval
HDRR combines document-level semantic routing with scoped chunk retrieval to outperform both pure chunk-based retrieval and semantic file routing on the FinDER benchmark, delivering higher average scores, lower failure rates, and more perfect answers.
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Zero-Shot Vulnerability Detection in Low-Resource Smart Contracts Through Solidity-Only Training
Sol2Vy transfers vulnerability detection from Solidity to Vyper in zero-shot fashion, outperforming prior methods on reentrancy, weak randomness, and unchecked transfers.
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Enhancing Financial Report Question-Answering: A Retrieval-Augmented Generation System with Reranking Analysis
Neural reranking in a hybrid RAG system raises high-quality answer rates from 33.5% to 49.0% on financial report questions.