ToxiREX is a new dataset of 128k Reddit comments in six languages with hierarchical annotations for implicit toxicity in conversational context based on an existing reasoning schema.
ACM Computing Surveys , volume=
9 Pith papers cite this work. Polarity classification is still indexing.
9
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2026 9verdicts
UNVERDICTED 9representative citing papers
ω-EVA is a three-stage latent world model framework that trains action-conditioned dynamics, a language-conditioned flow policy, and a tri-branch refiner to improve embodied action generation in simulation.
WorldEvolver uses episodic memory, semantic memory, and selective foresight to self-evolve world models at test time, achieving top prediction accuracy and agent success on ALFWorld and ScienceWorld benchmarks.
The FIL Hypothesis claims that inductive biases outperform purely data-driven methods on GPU programming tasks with non-trivial feedback loops.
Proposes a self-evolving cognitive framework integrating causal world modeling, intervention-driven reasoning, and continual refinement for embodied scientific intelligence.
A systematic review of text world models as transition predictors for LLM agents, organized by foundations, construction methods, applications in planning/training, and evaluation.
The paper delivers a multi-axis taxonomy for world models that maps architectures, training families, reasoning strategies, and domains from early cognitive foundations through systems such as Dreamer, MuZero, and Sora while noting evaluation gaps.
The paper describes an open-source web application that applies generative world models to produce interactive cinematic explorations of quantum computing hardware grounded in AWS Braket specifications.
A tutorial that unifies explicit and implicit world models through shared predictive structure for applications in physical AI such as robotics.
citing papers explorer
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ToxiREX: A Dataset on Toxic REasoning in ConteXt
ToxiREX is a new dataset of 128k Reddit comments in six languages with hierarchical annotations for implicit toxicity in conversational context based on an existing reasoning schema.
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Bridging the Agent-World Gap: Text World Models for LLM-based Agents
A systematic review of text world models as transition predictors for LLM agents, organized by foundations, construction methods, applications in planning/training, and evaluation.