"Transformer's 'Father' Blasts: Current AI Reaches Dead End, Fine - Tuning a Waste of Time!" - 36 Kr
<a href="https://news.google.com/rss/articles/CBMiU0FVX3lxTE5hMkxZVjl2dldyYjV4V1VZT1VtbGlCRlA2MkJVVkgydEF5cV9zbndheU90S3ItU1RtTVJLZ1AzMUhwekU0ei10X3JWUm90ODFqVy1B?oc=5" target="_blank">"Transformer's 'Father' Blasts: Current AI Reaches Dead End, Fine - Tuning a Waste of Time!"</a> <font color="#6f6f6f">36 Kr</font>
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Detecting collusion through multi-agent interpretability
TL;DR Prior work has shown that linear probes are effective at detecting deception in singular LLM agents. Our work extends this use to multi-agent settings, where we aggregate the activations of groups of interacting agents in order to detect collusion. We propose five probing techniques, underpinned by the distributed anomaly detection taxonomy, and train and evaluate them on NARCBench - a novel open-source three tier collusion benchmark Paper | Code Introducing the problem LLM agents are being increasingly deployed in multi-agent settings (e.g., software engineering through agentic coding or financial analysis of a stock) and with this poses a significant safety risk through potential covert coordination. Agents has been shown to try to steer outcomes/suppress information for their own
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In the current landscape of computer vision, the standard operating procedure involves a modular Lego-brick approach: a pre-trained vision encoder for feature extraction paired with a separate decoder for task prediction. While effective, this architectural separation complicates scaling and bottlenecks the interaction between language and vision. The Technology Innovation Institute (TII) research team is challenging [ ] The post TII Releases Falcon Perception: A 0.6B-Parameter Early-Fusion Transformer for Open-Vocabulary Grounding and Segmentation from Natural Language Prompts appeared first on MarkTechPost .
Peft 0.18.1 crashing when fine-tuning
Hi, peft Version: 0.18.1 is crashing when attempting to fine-tune google/gemma-4-E2B. The error msg is shown below. I checked and 0.18.1 is the latest version. Will there be an update soon or is there a workaround? I’d appreciate any help. thanks! ValueError: Target module Gemma4ClippableLinear( (linear): Linear(in_features=768, out_features=768, bias=False) ) is not supported. Currently, only the following modules are supported: `torch.nn.Linear`, `torch.nn.Embedding`, `torch.nn.Conv1d`, `torch.nn.Conv2d`, `torch.nn.Conv3d`, `transformers.pytorch_utils.Conv1D`, `torch.nn.MultiheadAttention.`. 1 post - 1 participant Read full topic
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Detecting collusion through multi-agent interpretability
TL;DR Prior work has shown that linear probes are effective at detecting deception in singular LLM agents. Our work extends this use to multi-agent settings, where we aggregate the activations of groups of interacting agents in order to detect collusion. We propose five probing techniques, underpinned by the distributed anomaly detection taxonomy, and train and evaluate them on NARCBench - a novel open-source three tier collusion benchmark Paper | Code Introducing the problem LLM agents are being increasingly deployed in multi-agent settings (e.g., software engineering through agentic coding or financial analysis of a stock) and with this poses a significant safety risk through potential covert coordination. Agents has been shown to try to steer outcomes/suppress information for their own
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