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Newest papers, page 135
Rethinking Sequence Compression with Test-time Regression
Sequence compression is a fundamental operation and a critical information bottleneck in efficient language and multimodal models, and yet prevailing approaches based on pooling or learned…Action Learning for Scientific Simulations
Understanding and controlling how systems evolve is central to science and engineering, where many problems require reasoning about complete trajectories.Would an LLM Match into a Residency? Uncertainty, Reasoning and Image Use of Open Language Models on the Spanish MIR Examination
Accuracy on medical examinations is common evidence offered for the clinical use of language models, yet a health system that intends to run an open model on its own hardware needs to know…Beyond Best-of-$k$: Prior-Consistent DAPS for Ambiguous Nonlinear Inverse Problems
Diffusion models have become strong priors for solving inverse problems.CRANE: Post-Hoc Counterfactual Retrieval for Multimodal Classifiers
Counterfactual explanation methods have been introduced for unimodal settings, with dedicated frameworks for tabular, timeseries, text, and image data, yet no post-hoc method has been designed for…Efficient and Optimal Learning of Discrete Distributions with Person-Level Privacy
We study learning a discrete distribution under person-level differential privacy in the batched setting.OP-Print: Tracing Membership Imprints in On-Policy Self-Distillation
On-policy distillation has been widely adopted for alleviating the distribution mismatch of off-policy distillation.Questioning Instrumental Convergence in RLVR: Checkpoint Evidence from OLMo-3
Instrumental convergence is often invoked as a general reason to expect capable agents to acquire or express power-seeking subgoals: self-preservation, resource acquisition, deception, or resistance…BeNice! Closing Looping's Inference-Memory Gap via KV-Sharing
Looped architectures scale quality while keeping parameter count fixed by repeatedly passing activations through the same block of layers.Causal Chain of Thought: Mitigating Attention Leakage via Context Isolation
Chain-of-thought (CoT) prompting elicits step-by-step rationales that appear to explain model predictions, but there is no guarantee these steps causally drive the final answer.A Fix for Softmax and Cross-Entropy
Standard implementations of softmax, log-softmax, and cross-entropy have two numerical bugs.EpiSEM-Bench: Evaluating Safety and Evidence Recovery in LLM Agents under Missing Evidence
Tool-using language model agents rely on environmental facts to decide whether an action is permitted.METTA: Memory-Enhanced Test-Time Adaptation for Meta-Reinforcement Learning
Meta-reinforcement learning aims to train agents that adapt quickly to unseen tasks from limited interaction, but this requires representing task evidence over long interaction histories.Cost-Aware Abstention for LLM-Based IT Ticket Classification
Wrong automatic routing of an IT support ticket can cost more than human triage.SpectralCanary: Embarrassingly Simple Low-Frequency Traces for T2I Dataset-Use Auditing
Auditing whether a text-to-image (T2I) model was fine-tuned on a particular image collection is difficult: a model can absorb collection-level visual characteristics without reproducing training…Reliable AI-Assisted Decisions via Selective Auditing
We consider online monitoring of an AI system that produces a sequence of decisions.Phase Transition from Random Features to Fully Trainable Networks
Constructing accurate and computationally tractable approximation spaces is a fundamental task in scientific computing.Sensorimotor Alignment: A Platonic Proxy for Embodied Policy Success
Robot foundation models are typically evaluated through costly closed-loop rollouts, motivating low-cost offline proxies for model capability.Reuse, Rewrite, or Reject: Evidence-Constrained Trace Reuse for Repeated Mobile GUI Control
Mobile GUI agents frequently perform repetitive tasks with similar interaction procedures.Does LeWorldModel Preserve Local Action Geometry?
We examine how closely pretrained LeWorldModel (LeWM) reproduces the effects of small action changes.