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Document numérisé · 1800 Gallica (BnF) FR

Cours de mathématiques

Document numérisé par la Bibliothèque nationale de France, publié en 1800. Thème : mathématiques. Consultable en ligne sur Gallica.

Bibliothèque nationale de France #Mathématiques
Document numérisé · 1800 Gallica (BnF) FR

Cours de mathématiques

Document numérisé par la Bibliothèque nationale de France, publié en 1800. Thème : mathématiques. Consultable en ligne sur Gallica.

Bibliothèque nationale de France #Mathématiques
Prépublication · 2026 arXiv EN

Can Language Models Play the Wikipedia Game?

Language models increasingly support or automate information retrieval from document collections too large to index. This task is difficult when it requires specialist linguistic or scientific knowledge. We used the Wikipedia Game to test language models on an...

Alexander Hickey, Joanna Knight et al. #cs.AI
Prépublication · 2026 arXiv EN

Hide and Seek: HIDE Concepts to SEEK explanations for black box models

Interpreting machine learning model predictions is a central challenge, particularly for black-box vision models. Concept-based attribution methods interpret models using human-understandable concepts. Existing concept-based methods can only interpret classifi...

Bhanu Tokas, Rahul Nair et al. #cs.CV
Prépublication · 2026 arXiv EN

RSI-Anything: Unlocking Recursive Self-Improvement with World Models

Recursive self-improvement (RSI) aims to transform interaction experience into persistent improvements, yet external feedback is costly and world-model predictions may become unreliable as policies evolve. We introduce RSI-Anything, a domain-general framework...

Taoyong Cui, Pinxian Zeng et al. #cs.CL
Prépublication · 2026 arXiv EN

Revisiting Tabular Deep Regression: Objectives and the Limits of Global Early Stopping

While deep learning models for tabular data have recently received significant research attention, the choice of objective functions for regression tasks remains an understudied degree of freedom. Several lines of research offer alternatives to the standard Me...

Danil Rudenko, Georgii Bulgakov et al. #cs.LG
Prépublication · 2026 arXiv EN

Structural Automata for Neural Semantic Parsing

Neural semantic parsers generate meaning representations token by token, yet well-formedness depends on references, scope, and graph relations that unfold during generation. Constrained decoding prevents locally invalid tokens but does not guarantee that a val...

Xiao Zhang #cs.CL
Prépublication · 2026 arXiv EN

Task Context Shapes Component Roles in Language Models

Large language models reuse the same attention heads across tasks, but identifying these shared heads does not explain what they do differently in each task. A natural source of inspiration is task-dependent interactions among shared brain regions, which motiv...

Sovesh Mohapatra, Dani S Bassett #cs.CL
Prépublication · 2026 arXiv EN

RATED: Reliability-Aware AI Agent Tool Retrieval via Execution Dynamics

As AI agents increasingly rely on external tools, accurate retrieval is essential for reliable behavior. Existing methods optimize semantic relevance but largely ignore tool availability during execution. To address this gap, we propose RATED (Reliability-Awar...

Weiliang Chen, Song Liao #cs.AI
Prépublication · 2026 arXiv EN

X-AgentRed: Red-Teaming Personal Agents in Evolving Multi-Service Ecosystems

Personal agents increasingly connect to services across the web and applications by using tools. As the effects of their actions accumulate and interact across services, unintended or harmful outcomes can arise when agents fulfill benign user requests. Proacti...

Yeonsung Jung, Zhiyuan Wang et al. #cs.AI