Leaderboards, eval harnesses and ablations — the contested business of deciding which model is actually better.
arXiv:2510. 11014v2 Announce Type: replace-cross Abstract: Autonomous robots often view rooms only partially, through a doorway, where the walls and scene structure hide the geometry and task-relevant semantics needed for safe navigation and goal-directed action.
arXiv:2606. 06615v1 Announce Type: cross Abstract: Retrieving music using natural language descriptions has improved with contrastive audio-text models such as CLAP, but current systems remain limited to coarse semantic queries.
arXiv:2605. 25638v2 Announce Type: replace-cross Abstract: Policy loss estimation remains a fundamental and long-standing challenge in reinforcement learning (RL) for diffusion language models (DLMs).
arXiv:2606. 07032v1 Announce Type: cross Abstract: Zero-Shot Composed Image Retrieval (ZS-CIR) aims to retrieve a target image based on a query composed of a reference image and a relative caption without training samples.
arXiv:2603. 13546v2 Announce Type: replace Abstract: We introduce Probabilistic Gaussian Homotopy (PGH), a probability-space continuation framework for nonconvex optimization.
arXiv:2606. 06527v1 Announce Type: cross Abstract: Energy-efficient edge inference requires reducing arithmetic cost, memory traffic, and hardware overhead.
arXiv:2605. 17561v2 Announce Type: replace-cross Abstract: Issues faced when using software are reported in the form of bug reports.
arXiv:2606. 07001v1 Announce Type: cross Abstract: High-quality training data is essential to large language models (LLMs) and typically requires extensive and costly manual curation.
arXiv:2606. 07368v1 Announce Type: cross Abstract: Automated mitosis detection is a well-established task in computational pathology.
arXiv:2606. 07033v1 Announce Type: new Abstract: Open-vocabulary audio-visual event localization (OV-AVEL) jointly models audio-visual cues to recognize and temporally localize events, including categories unseen during training.
arXiv:2512. 13278v2 Announce Type: replace-cross Abstract: Agentic reinforcement learning has advanced large language models (LLMs) to reason through long chain-of-thought trajectories while interleaving external tool use.
arXiv:2606. 07474v1 Announce Type: new Abstract: Unsupervised Continual Learning (UCL) aims to enable neural networks to learn sequential tasks without labels or access to past data.
arXiv:2606. 06920v1 Announce Type: cross Abstract: Deploying Small Language Models (SLMs) on edge devices requires efficient fine-tuning strategies that adapt models to new tasks without degrading their general capabilities.
arXiv:2606. 06744v1 Announce Type: new Abstract: Two-sided matching markets often involve information that unfolds over time through interviews, repeated interaction, learning, and separation.
arXiv:2505. 10892v2 Announce Type: replace Abstract: Post-training LLMs with RLHF and preference optimization methods (e.
arXiv:2606. 07365v1 Announce Type: cross Abstract: Photoplethysmography (PPG), a non-invasive measure of changes in blood volume, is widely used in both wearable devices and clinical settings.
arXiv:2606. 06899v1 Announce Type: cross Abstract: Variations in illumination remain a major challenge for visual representation learning, as they induce substantial appearance changes both across and within environments.
arXiv:2606. 07237v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in healthcare for tasks such as clinical question answering, diagnosis support, and report summarization.
arXiv:2606. 06682v1 Announce Type: new Abstract: Missing data is a common challenge in spatiotemporal systems, arising in applications such as air quality monitoring and urban traffic management.
arXiv:2603. 24576v2 Announce Type: replace-cross Abstract: Robots often observe information that determines a future action long before that action is executed.