Claims Browser

World Action Models augment robot policies by predicting how task-relevant scene states may evolve under interaction

"World Action Models (WAMs) augment robot policies by predicting how task-relevant scene states may evolve under interaction."

Recent World Action Models increasingly perform prediction in latent representation spaces, avoiding full appearance-level generation while preserving control-relevant information

"Recent WAMs increasingly perform such prediction in latent representation spaces, avoiding full appearance-level generation while preserving control-relevant information."

LEON improves closed-loop performance and robustness in World Action Models across two formulations while remaining effective under full transition replacement

"Across two WAM formulations that integrate latent prediction into the policy differently, LEON improves closed-loop performance and robustness while remaining effective under full transition replacement."

LLM agents increasingly rely on generated interaction data to learn how to interact with external environments

"LLM agents increasingly rely on generated interaction data to learn how to interact with external environments."

The field shows a shift toward execution-grounded accuracy, learner-relative complexity, and diversity beyond surface variation or dataset size

"The literature reveals a shift toward execution-grounded accuracy, learner-relative complexity, and diversity beyond surface variation or dataset size."

Latent chain-of-thought models improve compactness by moving intermediate reasoning from emitted text into continuous states, but this hides the causal object.

"Latent chain-of-thought models move intermediate reasoning from emitted text into continuous states, improving compactness but hiding the causal object."

SCIT (Suffix Cache Interchange Test) can identify which transformer object carries counterfactual computation through causal protocols that construct exact source-recipient counterfactuals and patch cache segments.

"We introduce SCIT, the Suffix Cache Interchange Test, a causal protocol that constructs exact source-recipient counterfactuals, patches declared cache segments, and identifies which transformer object carries the counterfactual computation."

In CODI-GPT2 and Sim-CoT-style GPT-2 models, counterfactual arithmetic transfers primarily through value-cache suffix trajectories rather than through hidden states, keys, reusable answer slots, or single-token triggers.

"On CODI-GPT2 and a Sim-CoT-style GPT-2 reproduction, counterfactual arithmetic transfers primarily through value-cache suffix trajectories rather than hidden states, keys, reusable answer slots, or single-token triggers."

SCIT reveals carrier-regime shifts where arithmetic-like GPT-2/1B cells preserve latent-tail value/KV transfer, while competent 8B and repaired non-arithmetic cells route through prompt-prefix or full-cache K/V instead.

"SCIT reveals carrier-regime shifts: arithmetic-like GPT-2/1B cells preserve latent-tail value/KV transfer, whereas competent 8B and repaired non-arithmetic cells route through prompt-prefix or full-cache K/V"

Vision generative AI has emerged as one of the most rapidly advancing areas of deep learning

"Vision generative artificial intelligence (AI) has emerged as one of the most rapidly advancing areas of deep learning."

PDPO (Planning Diffusion Policy Optimization) achieves an improved success rate over strong baselines in crowd navigation tasks

"Experiments show that PDPO obtains an improved success rate over strong baselines"

Prediction of Prediction (PoP) achieves 75.5% AUROC for factual-correctness classification on TruthfulQA

"PoP achieves an area under the receiver operating characteristic curve (AUROC) of 75.5% for factual-correctness classification"

Frontier AI model performance is achievable by a wide range of institutions through continual learning on open-weight models, at substantially lower compute and personnel budgets than commonly thought

"frontier performance is achievable by a wide range of institutions through Continual Learning on readily available open-weight models"

The continual learning approach yields gains comparable to those typically seen across multiple successive model generations

"This yields gains comparable to those typically seen across multiple successive model generations, at compute and personnel budgets substantially lower than commonly thought"

Thomson model performs competitively with recent frontier models across agentic tasks, safety, legal, tax, multilingualism, and large-scale Deep Research

"Thomson performs competitively with recent frontier models across agentic tasks, safety, legal, tax & multilingualism, and large-scale Deep Research"

The approach almost completely eliminates the forgetting problem common to narrow domain adaptation while improving capabilities across a wide range

"distinct improvements across a wide range of capabilities, including those not explicitly targeted, while almost completely eliminating the forgetting problem common to narrow domain adaptation"

Conversational AI systems such as chatbots and virtual assistants are becoming increasingly important to digital business processes

"Conversational AI systems, such as chatbots and virtual assistants, are becoming increasingly important to digital business processes."

The BPMN4CAI extension facilitates adaptive decision-making processes, robust context management, and transparent interactions for Conversational AI within business processes

"The results show that the BPMN4CAI extension facilitates adaptive decision-making processes, robust context management, and transparent interactions for Conversational AI within business processes."