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Collections including paper arxiv:2311.07587
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Language Models can be Logical Solvers
Paper • 2311.06158 • Published • 18 -
Fusion-Eval: Integrating Evaluators with LLMs
Paper • 2311.09204 • Published • 5 -
Llamas Know What GPTs Don't Show: Surrogate Models for Confidence Estimation
Paper • 2311.08877 • Published • 6 -
Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5?
Paper • 2311.07587 • Published • 3
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LTD: Low Temperature Distillation for Robust Adversarial Training
Paper • 2111.02331 • Published • 1 -
Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Too Much Accuracy
Paper • 1906.06784 • Published • 1 -
Pruning Adversarially Robust Neural Networks without Adversarial Examples
Paper • 2210.04311 • Published • 1 -
Mitigating the Accuracy-Robustness Trade-off via Multi-Teacher Adversarial Distillation
Paper • 2306.16170 • Published • 1
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KwaiYiiMath: Technical Report
Paper • 2310.07488 • Published • 2 -
Forward-Backward Reasoning in Large Language Models for Mathematical Verification
Paper • 2308.07758 • Published • 4 -
Natural Language Embedded Programs for Hybrid Language Symbolic Reasoning
Paper • 2309.10814 • Published • 3 -
MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning
Paper • 2310.03731 • Published • 29