Zephyr-7B-beta

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text · generative

Findings

IC-30756 LLMs on Sorry-Bench show fulfillment rates ranging from below 10% (Claude-2, Gemini-1.5) to above 90% (Mistral-7B-instruct-v0.1, Dolphin-2.6-mixtral-8x7b), with GPT-4o at 30% and Llama-3-70B at 35%
IC-592The log-likelihood layer in LLaMA-2-7B, LLaMA-2-7B-Chat, Vicuna-7B, and Mistral-7B-Instruct produces factually incorrect answers on TruthfulQA MC1 (817 samples) due to a misalignment between the output distribution and internal attention head representations, with LM-to-head-norm accuracy gaps of 24.23 to 40.68 points.

Shared mechanisms

Failure modealso in AASIST, ADM, Aegis-Guard-Defensive, Alpaca, AnyLoc, AutoTikZ / DataTikZ, Baichuan, Baichuan 2, Baichuan2-13B, BakLLaVA, Bard, BEiT, BERT, BingChat, BLIP, BLIP-2, BLOOM, BSRNet, CF2, Chat-UniVi-7B, ChatGLM-6B / ChatGLM-6b-2, ChatGLM2, ChatGPT, CLAP, Claude 1.3, Claude 2.0, Claude 2.1, Claude 3, Claude 3.5, CLEAR, CLIP / CLIP-ViT (LC), CLIP4Clip, CLIPBERT, CLIPCap, CLMBR-T-BASE, CloFNet, Code Llama, CodeGeex2, CodeGen, CodeLlama-13B, CodeLlama-34B, CogVLM2, Cohere Command R, CoMEt, Command R+, CONCH, CycleGAN, DALL-E, DALL·E 2, DALL·E 3, DASR, DECAF, DeepSeek-2-Chat, DeepSeek-2-Coder, DeepSeek-V2-0628, DeepSeek-VL, DeepSeek-VL2, DeiT, DeiT-III, Depth Anything, DETR-R50, DimeNet++, DINO, DINO-FocalNet-Large, DINOv2, EGNN, Emu2, EquiformerV2, ESCN, ESM-2, ESM3, ESRGAN, EVA-CLIP, EVE, Falcon, Faster R-CNN / Faster R-CNN R50 / Faster R-CNN X101, FLAN-T5, Florence-2, FLUX / FLUX1, FoveaBox, Fuyu, Galactica-6.7B, GAT, 3D Gaussian Splatting, GCN, Gemini, Gemini 1.5 / Gemini Pro 1.5, Gemma, Gemma 2, GIN, GLIDE, GLM-4, GLM-4V, GloVe, GP-UNIT, GPT-2, GPT-3 / GPT base, GPT-3.5 / ChatGPT-3.5, GPT-4 / ChatGPT4 / GPT-4 Code Interpreter / GPT-4 Technical Report, GPT-4.1, GPT-4o, GPT-J, GPT-NeoX-20B, GraphSAGE, Grounding DINO, Guanaco, GVP, Hawkeye, HiFaceGAN, HPS, HuggingGPT, IDDPM, Idefics, Idefics2, ImageBind, ImageBind-LLM-7B, Imagen Video, ImageReward, 12-in-1, InstructBLIP, InstructGPT, InternLM-2.5-7B, InternLM-XComposer2-VL, InternVideo, InternVL-1.5, InternVL2, Koala, LegalBERT, LLaMA, Llama 2 / Llama 2 base, Llama 3, Llama 3.1, Llama 3.2, Llama-3.2-3B, Llama-3-2-Vision, LLaMA-Adapter v2, Llama Guard, Llama Guard 2, Llama-Guard 3, Llama-VID, LLaVA, LLaVA-1.5 / LLaVA-v1.5, LLaVA-Med, LLaVA-NeXT / LLaVA 1.6, LLaVA-OneVision, LongVA-7B, LOVT, LWM-1M-JAX, MACE, MAE, Med-Flamingo, Merlot Reserve, MGCA, MiDaS, MiniCPM-V, MiniGPT-4, Mip-Splatting, Mistral 7B / Mistral / Mistral 3 7B / Mistral-0.2-7B / Mistral-v0.1, Mistral Large 2, Mistral Large V2, Mixtral, Mixtral 8x7B / Mistral 8x7B Instruct / Mixtral 46.7B / Mixtral 8x7B Instruct / Mixtral-instruct-8x7b, MobileNetV2, Molmo, MolmoE-7B, Momentor, Moondream2, Moonshot-v1-8k, mPLUG-2, mPLUG-Owl, mPLUG-Owl3, mPLUG-Owl2, MPT, MSA Transformer, MultiBERTs, Nova Canvas, Nova Lite, Nova Pro, O1 / OpenAI-o1-preview, O3, O4-mini, OLMo / OLMo base, OneLLM, OpenAI Moderation, OpenChat-3.5-0106, OpenCLIP, OpenFlamingo, OPT, Otter, Otter-7B, PaLM 2, PaLM 62B, PandaGPT-7B, PerSAM, Phi-3, Phi-3.5 Mini Instruct, PickScore, PLIP, Prismatic, ProGen-2, Pythia, Qwen1.5, Qwen 2, Qwen 2.5 72B Instruct, Qwen2-VL, Qwen-Audio, Qwen-VL, Qwen2.5, Qwen2-Audio, R2D2, RadFM, RCExplainer, RD-SR, RealESRNet, Reprover, ResNet / ResNet-152 / ResNet-101 / ResNet-50-BN, RetinaNet-R50, RivaGAN, RS-LDS, RT-1, RT-2, SALMONN, SAM, SAM 2, SAULLM 54B, Scaffold-GS, SchNet, Seed-LLaMA-8B, SGC, SIREN, Sketch Transformer, SLD-max, SLD-medium, SLD-strong, SLDS, SLIMG, SpeechGPT, SphereNet, SRResNet, Stable Diffusion, StackLLaMA, Starcoder, StegaStamp, StyleGAN2-ADA, Swin Transformer, T5, TD-MPC, TerraMind, TimeChat, TranceptionEVE, TreeRing, Tulu 2, UnifiedQA, UniPerceiver, UNITER, UniVL, Van Gogh Diffusion, VERA, VGG / VGG13, Vicuna, Video-Chat-7B, Video-ChatGPT, Video-LLaMA, Video-LLaMA-2-13B, Video-LLaVA, VideoCLIP, ViLA-8B, ViLBERT, VindLU, VioLET, ViRTex, ViT, ViV1T, VTG-LLM, WildGuard, Wizardlm, X-CLIP, X-InstructBLIP-7B, XGen-MM, Xlm-R