Our benchmark for multimodal unlearning methods
Alexey Dontsov
therem
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paper
about 9 hours ago
Emergent Misalignment via In-Context Learning: Narrow in-context
examples can produce broadly misaligned LLMs
authored
a paper
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OrtSAE: Orthogonal Sparse Autoencoders Uncover Atomic Features
Organizations
models
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therem/gemma_2_2b_matryoshka_sae
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therem/llava-1.5-7b-CLEAR-forget-scrub
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therem/llava-1.5-7b-CLEAR-forget-retain_ft
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therem/llava-1.5-7b-CLEAR-forget-LLMU
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therem/llava-1.5-7b-CLEAR-forget-KL
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therem/llava-1.5-7b-CLEAR-forget-idk
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therem/llava-1.5-7b-CLEAR-forget-grad_ascent
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therem/llava-1.5-7b-CLEAR-forget-DPO
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therem/llava-1.5-7b-CLEAR-finetune
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therem/gpt_imdb_jsd_beta1
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datasets
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therem/all_math_generations
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therem/deepseek_ai_deepseek_math_7b_instructHuggingFaceH4_MATH_500
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therem/qwen3_math_ai_minervamath_4x
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therem/qwen3_math_ai_olympiadbench_4x
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therem/qwen3_HuggingFaceH4_MATH_500_4x
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therem/qwen_math_math_ai_minervamath_8x
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therem/qwen_math_math_ai_olympiadbench_8x
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therem/qwen_math_HuggingFaceH4_MATH_500_8x
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therem/deepseek_r1_math_ai_minervamath_4x
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therem/deepseek_r1_math_ai_olympiadbench_4x
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