Users praise GLM 5.2 for its direct, unflinching attitude, contrasting it with more saccharine US models. The author speculates this behavior stems from culturally specific training data, suggesting local datasets have a stronger influence than previously assumed.
GLM 5.2's Attitude Reflects Cultural Training Influences
Single-direction attack on GLM-5.3-Flash reveals safety alignment fragility in MoE models
Researchers demonstrate that directional ablation, a white-box attack removing refusal by projecting out a single direction from weights, remains effective on frontier mixture-of-experts (MoE) models like GLM-5.3-Flash. The study shows that while the attack survives the architecture, its effects are distributed across attention, dense, and routed-expert writers rather than concentrated in one location.
ntrillard finds largest coordinates not driving Qwen2-1.5B logit steering
A causal investigation of vocabulary-logit steering on the Qwen2-1.5B model reveals that the largest coordinates in the steering vector are not necessarily responsible for the observed behavioral effects. The study, conducted by ntrillard, analyzes how sparse ranked logit steering influences token generation and identifies the specific structural components that drive these changes.
WebWorld uses browser-as-world-model to self-improve web code
The authors present WebWorld, an interface that allows a Vision-Language Model (VLM) to interact autonomously with the browser as a deterministic world model for web code. This approach addresses the structural flaw in VLM-driven self-improvement where the model judges its own repairs by introducing a counterparty that cannot be fooled.
Gemma 4 baseline trace shows hallucination loop and self-report
A baseline trace of Gemma 4 with zero force cap reveals a persistent hallucination loop where the model generates a self-report of failure before entering a repetition well. The telemetry confirms that role-tag bleed and phrases like "STOPITSTOP" occur within this unstable state, mirroring patterns observed in Llama and Gemma 3 loaders since December 2025.
Study finds progressive representational structuring across depth in 8 open models
A new preprint analyzes hidden-state dynamics in eight locally instrumented small open Transformer models to determine if internal representations follow a structured progression during inference. The study distinguishes between changes occurring across model depth and those evolving over autoregressive generation time.