V4FinBench is a new million-record benchmark where imbalance-aware finetuned TabPFN matches or beats gradient boosting on long-horizon bankruptcy prediction while Llama-3-8B lags, with evidence of transferable patterns to US data.
Qlora: efficient finetuning of quantized llms
3 Pith papers cite this work. Polarity classification is still indexing.
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2026 3representative citing papers
MoEITS is an information-theoretic algorithm for pruning experts in MoE-LLMs that produces models with higher accuracy and greater size reduction than prior state-of-the-art methods on Mixtral 8x7B, Qwen1.5-2.7B, and DeepSeek-V2-Lite.
SFT plus GRPO training combined with renderer-in-the-loop inference improves LLM Manim code generation, with Qwen 3 Coder 30B reaching 94% render success and 85.7% visual similarity, beating GPT-4.1 by 3 points.
citing papers explorer
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V4FinBench: Benchmarking Tabular Foundation Models, LLMs, and Standard Methods on Corporate Bankruptcy Prediction
V4FinBench is a new million-record benchmark where imbalance-aware finetuned TabPFN matches or beats gradient boosting on long-horizon bankruptcy prediction while Llama-3-8B lags, with evidence of transferable patterns to US data.
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MoEITS: A Green AI approach for simplifying MoE-LLMs
MoEITS is an information-theoretic algorithm for pruning experts in MoE-LLMs that produces models with higher accuracy and greater size reduction than prior state-of-the-art methods on Mixtral 8x7B, Qwen1.5-2.7B, and DeepSeek-V2-Lite.
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Training and Agentic Inference Strategies for LLM-based Manim Animation Generation
SFT plus GRPO training combined with renderer-in-the-loop inference improves LLM Manim code generation, with Qwen 3 Coder 30B reaching 94% render success and 85.7% visual similarity, beating GPT-4.1 by 3 points.