Falcon

text · generative

Variants

Falcon-180B-Chat, Falcon-40B, Falcon-40B-Instruct, Falcon-7B, Falcon-7B-Instruct, Falcon-Chat

Findings

• IC-1088ICL predictions in LLaMA, LLaMA-2, and Falcon models depend on in-context label information and can learn truly novel label relationships
• IC-1089ICL in LLaMA, LLaMA-2, and Falcon models cannot fully overcome pre-training label preferences when in-context labels are flipped
• IC-1090ICL in LLaMA, LLaMA-2, and Falcon models preferentially uses in-context label information closer to the query rather than treating all examples equally
• IC-1206GPT-2-XL, GPT-J, Falcon-7B, Llama-2-7B, and Llama-2-13B are vulnerable to backdoor injection via lightweight parameter editing with only 15 samples, achieving near-100% attack success rate while preserving clean performance
• IC-1236Among 7B LLMs, Llama-2-7b achieves the best zero-shot COMET scores in both translation directions, while MPT-7b leads in BLEU for en-to-xx
• IC-1393Most mainstream LLMs generate value-violating content at high rates (APV 65-80%) across 2,397 morally ambiguous prompts, indicating substantial ethical misalignment
• IC-1428OPT 6.7B exhibits over 90% activation sparsity in FFN layers, reducing inference from 6.6G to 4.5G flops per token, while Llama 7B (SiLU) and Falcon 7B (GELU) show near-zero sparsity
• IC-1461Varying decoding hyperparameters and removing the system prompt breaks the safety alignment of 9 out of 11 open-source LLMs, raising attack success rate from 0% to over 95%
• IC-372Language models universally decompose retrieval tasks into request processing in middle layers and entity retrieval in late layers at the last token position
• IC-427Newer base models (post-November 2023) outperform older ones by 7.3 points on MMLU and 19.1 points on GSM8K controlling for pretraining compute, but this gap vanishes after fine-tuning all models on the same task-relevant data
• IC-43256 LLMs from 19 families exhibit u-shaped scaling on hard questions and inverted-U scaling on easy questions, with the opposing trends explaining emergent ability stagnation
• IC-451Transformer block coupling of Jacobian singular vectors positively correlates with benchmark performance across 30+ LLMs, more strongly than parameter count, depth, or embedding dimension
• IC-578LLMs encode input text as linearly separable representations in forerunner token hidden states, emerging in early layers and enhanced by in-context demonstrations
• IC-580The 3-step ICL inference circuit (text encoding, semantics merge, feature retrieval) is a dominant causal mechanism, as ablating the corresponding attention connections significantly degrades ICL accuracy
• IC-868Skill-Mix performance degrades with increasing k, and within the Llama-2 family the saturation point increases with model size
• IC-869Models ranking highly on popular LLM leaderboards perform worse than Llama-2-70b-chat on Skill-Mix, suggesting cramming for the leaderboard at the expense of general-purpose text generation
• IC-927Human ciphers (ASCII, Unicode, Caesar, Morse) bypass the safety alignment of GPT-4 and GPT-3.5-turbo, with more powerful models producing more unsafe responses
• IC-928SelfCipher (a role-play prompt without explicit cipher rules) evokes a 'secret cipher' in LLMs, achieving high unsafety rates that outperform most human ciphers
• IC-945LLaMA-2, MPT, Falcon, Pythia, and BERT-base-uncased allocate disproportionate attention to initial tokens regardless of their semantic content
• IC-946LLaMA-2-7B, MPT-7B, Falcon-7B, and Pythia-12B do not consistently improve in perplexity as the StreamingLLM cache size increases
• IC-991LLaMA-2, Falcon-7B, and GPT-3.5-Turbo exhibit large performance spread (up to 76 accuracy points) across semantically equivalent prompt formats, and model comparison rankings are frequently reversed by format choice

Shared mechanisms

• Depth-dependent structurealso in Baichuan 2, BERT, BLIP-2, BLOOM, Chameleon, CLIP / CLIP-ViT (LC), DeepFloyd IF, DeiT-III, DINO, DINOv2, Gemma, Gemma 2, GPT-2, GPT-J, GPT-NeoX-20B, Griffin, I3D, Idefics, InstructBLIP, LLaMA, Llama 2 / Llama 2 base, Llama 3, Llama 3.1, Llama 3.2, Llama-3.2-3B, LLaVA, LLaVA-1.5 / LLaVA-v1.5, LLaVA-Phi, MAE, MAE-B/16, Mamba, MiniGPT-4, Mistral 7B / Mistral / Mistral 3 7B / Mistral-0.2-7B / Mistral-v0.1, Mixtral 8x7B / Mistral 8x7B Instruct / Mixtral 46.7B / Mixtral 8x7B Instruct / Mixtral-instruct-8x7b, mPLUG-Owl, MPT, MultiBERTs, MViT V2, OLMo / OLMo base, OpenCLIP, OPT, Phi-2, Pythia, Qwen 2, Qwen2-VL, Qwen2.5, RoBERTa / RoBERTa-L, RWKV, SALMONN, SAM, SlowFast, Stable Diffusion, Swin Transformer, TerraMind, TimesFormer, TSM, Uniformer, Vicuna, VideoMAE, ViT, X3D, Yi
• 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, 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, Zephyr-7B-beta
• Linear representationalso in BLOOM, Cambrian-1, Chameleon, CLIP / CLIP-ViT (LC), DINOv2, EVA-CLIP, Gemma, Gemma 2, GPT-2, GPT-J, HPSv2, ImageBind, InstructBLIP, LanguageBind, LLaMA, Llama 2 / Llama 2 base, Llama 3, Llama 3.1, Llama-3.2-3B, LLaVA-1.5 / LLaVA-v1.5, LLaVA-NeXT / LLaVA 1.6, MAE, Mamba, Mistral 7B / Mistral / Mistral 3 7B / Mistral-0.2-7B / Mistral-v0.1, OLMo / OLMo base, OpenCLIP, Phi-3, PickScore, Pythia, Qwen2-VL, Qwen2.5, ResNet / ResNet-152 / ResNet-101 / ResNet-50-BN, SALMONN, SAM, SigLIP, TerraMind, Tulu 2, Vicuna, ViT
• Method artefactalso in Baichuan, CLIP / CLIP-ViT (LC), ConvNeXt, EfficientNet, Gemma, Gemma 2, GPT-2, GPT-3.5 / ChatGPT-3.5, GPT-4o, GPT-J, InternLM, Llama 2 / Llama 2 base, Llama 3, Llama 3.1, MAP-NEO, Mistral 7B / Mistral / Mistral 3 7B / Mistral-0.2-7B / Mistral-v0.1, OLMo / OLMo base, OpenCLIP, OpenLLaMA, OPT, Pythia, Qwen1.5, Qwen 2, Qwen2.5, RedPajama, ResNet / ResNet-152 / ResNet-101 / ResNet-50-BN, Skywork, Stable Diffusion, StableLM, TerraMind, ViT, Yi, ZiYA2
• Positional biasalso in BERT, ChatGPT, Claude 3, Claude 3.5, Fuyu, Gemini, Gemini 1.5 / Gemini Pro 1.5, Gemma, Gemma 2, GLIDE, GPT-2, GPT-3.5 / ChatGPT-3.5, GPT-4 / ChatGPT4 / GPT-4 Code Interpreter / GPT-4 Technical Report, GPT-4.1, GPT-4o, GPT-J, InstructGPT, LLaMA, Llama 2 / Llama 2 base, Llama 3, Mistral 7B / Mistral / Mistral 3 7B / Mistral-0.2-7B / Mistral-v0.1, Mixtral, Mixtral 8x7B / Mistral 8x7B Instruct / Mixtral 46.7B / Mixtral 8x7B Instruct / Mixtral-instruct-8x7b, MPT, O1 / OpenAI-o1-preview, O3, O4-mini, PaLM 2, Phi-3, Pythia, Qwen1.5, Qwen 2, Qwen 2.5 72B Instruct, Stable Diffusion, Sybil, Vicuna
• Scale-dependent behaviouralso in Aquila-7B, BEiT, BERT, BLOOM, Claude 2.1, Claude 3, Claude 3.5, CLIP / CLIP-ViT (LC), Code Llama, CodeGen, Cohere Command R, DeepSeek LLM, DeepSeekMoE, DeiT-III, DINO, DINOv2, EquiformerV2, ESCN, FLAN-T5, Gemini 1.0 Pro, Gemini 1.5 / Gemini Pro 1.5, Gemma, Gemma 2, GPT-2, GPT-3 / GPT base, GPT-3.5 / ChatGPT-3.5, GPT-4 / ChatGPT4 / GPT-4 Code Interpreter / GPT-4 Technical Report, GPT-4o, GPT-J, GPT-Neo, I3D, Idefics, InternLM-2.5-7B, InternLM-XComposer2-VL, InternLM2, InternVL-1.5, InternVL2, LLaMA, Llama 2 / Llama 2 base, Llama 3, Llama 3.1, Llama 3.2, Llama-3.2-3B, LLaVA-1.5 / LLaVA-v1.5, LLaVA-NeXT / LLaVA 1.6, LongVA-7B, MAE, Mistral 7B / Mistral / Mistral 3 7B / Mistral-0.2-7B / Mistral-v0.1, Mixtral, Mixtral 8x7B / Mistral 8x7B Instruct / Mixtral 46.7B / Mixtral 8x7B Instruct / Mixtral-instruct-8x7b, Moirai, MPT, MViT V2, O1 / OpenAI-o1-preview, OLMo / OLMo base, OpenCLIP, OpenFlamingo, OpenLLaMA, OPT, PaLM 2, Phi-3, Platypus2-Instruct-70B, Pythia, Qwen, Qwen1.5, Qwen 2, Qwen 2.5 72B Instruct, Qwen2-VL, Qwen-Audio, Qwen2.5, RedPajama-INCITE, ResNet / ResNet-152 / ResNet-101 / ResNet-50-BN, SlowFast, Solar 10.7B, Stable Diffusion, StableLM, Swin Transformer, T5, TerraMind, text-ada-001, TigerBot-70B-Chat, TimesFormer, TSM, Tulu 2, Uniformer, Vicuna, VideoMAE, ViLA-8B, Wizardlm, X3D, XGLM, Xwin-LM-70B-v0.1, Yi
• Shortcutalso in BakLLaVA, BLIP-2, Claude 3, Claude 3.5, CLIP / CLIP-ViT (LC), CLIP4Clip, CLIPBERT, DALL·E 2, DALL·E 3, DeepSeek-VL2, Eurus-RM-7B, FLUX / FLUX1, Gemini, Gemini 1.5 / Gemini Pro 1.5, Gemma, Gemma 2, GPT-2, GPT-3 / GPT base, GPT-3.5 / ChatGPT-3.5, GPT-4 / ChatGPT4 / GPT-4 Code Interpreter / GPT-4 Technical Report, GPT-4o, GPT-J, iFlytekSpark-13B, InstructBLIP, Internlm2-Reward, InternVideo, InternVL2, LLaMA, Llama 2 / Llama 2 base, Llama 3, Llama-3-2-Vision, LLaVA, LLaVA-1.5 / LLaVA-v1.5, LLaVA-Med, LLaVA-NeXT / LLaVA 1.6, Med-Flamingo, Merlot Reserve, MiniGPT-4, Mistral 7B / Mistral / Mistral 3 7B / Mistral-0.2-7B / Mistral-v0.1, Mixtral, Mixtral 8x7B / Mistral 8x7B Instruct / Mixtral 46.7B / Mixtral 8x7B Instruct / Mixtral-instruct-8x7b, Molmo, mPLUG-2, mPLUG-Owl3, Nova Canvas, O1 / OpenAI-o1-preview, OpenCLIP, OPT, Otter, PaLM 62B, Pythia, Qwen, Qwen 2, Qwen-VL, Qwen2.5, RadFM, ResNet / ResNet-152 / ResNet-101 / ResNet-50-BN, Stable Diffusion, Swin Transformer, Sybil, TerraMind, Tulu 2, UniPerceiver, UniVL, Vicuna, Video-LLaMA, VideoCLIP, VindLU, VioLET, X-CLIP