Newest with code · page 7
Every paper with a repository link. Each page shows two streams, newest first within each, counted separately: papers newer than the archive snapshot come from Syntology's graph Syntology; the rest are archive rows archive 2025-07-28. The two are never added together.
Newer than the archive snapshot Syntology
Cards 91–105 of 9,581 graph papers newer than 2025-07-28; this feed shows the newest 150, newest arXiv id first. Dates and the abstract sentence are from arXiv's metadata (CC0) for 9,280 of 9,581; for the other 301 the month is read from the id.
From the archive archive 2025-07-28
Cards 91–105 of 218,469 archive papers with a code link; this feed shows the newest 150, archive date first (newest archive date 2025-09-24). Within a month, dated rows come first, then the 49,179 undated rows placed by the month in their arXiv id. 4 archive rows carry a date after the snapshot and are placed by that date. 382 archive papers with neither a date nor an arXiv id cannot be placed and are not listed. 1 code-linked slug has no paper row in the archive and is not listed (so 218,469 listed + 382 unplaceable + 1 = 218,852 papers with code).
REST: Stress Testing Large Reasoning Models by Asking Multiple Problems at Once
Recent Large Reasoning Models (LRMs) have achieved remarkable progress on task-specific benchmarks, yet their evaluation methods remain constrained by isolated problem-solving paradigms.
Graph World Model
World models (WMs) demonstrate strong capabilities in prediction, generation, and planning tasks.
WildFX: A DAW-Powered Pipeline for In-the-Wild Audio FX Graph Modeling
Despite rapid progress in end-to-end AI music generation, AI-driven modeling of professional Digital Signal Processing (DSP) workflows remains challenging.
Reasoning or Memorization? Unreliable Results of Reinforcement Learning Due to Data Contamination
The reasoning capabilities of large language models (LLMs) have been a longstanding focus of research.
4D-Animal: Freely Reconstructing Animatable 3D Animals from Videos
Existing methods for reconstructing animatable 3D animals from videos typically rely on sparse semantic keypoints to fit parametric models.
Text-Visual Semantic Constrained AI-Generated Image Quality Assessment
With the rapid advancements in Artificial Intelligence Generated Image (AGI) technology, the accurate assessment of their quality has become an increasingly vital requirement.
Test-Time Canonicalization by Foundation Models for Robust Perception
Real-world visual perception requires invariance to diverse transformations, yet current methods rely heavily on specialized architectures or training on predefined augmentations, limiting generalization.
Bridging Robustness and Generalization Against Word Substitution Attacks in NLP via the Growth Bound Matrix Approach
Despite advancements in Natural Language Processing (NLP), models remain vulnerable to adversarial attacks, such as synonym substitutions.
Domain Borders Are There to Be Crossed With Federated Few-Shot Adaptation
Federated Learning has emerged as a leading paradigm for decentralized, privacy-preserving learning, particularly relevant in the era of interconnected edge devices equipped with sensors.
DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation
Pixel-level annotation is expensive and time-consuming.
Glance-MCMT: A General MCMT Framework with Glance Initialization and Progressive Association
We propose a multi-camera multi-target (MCMT) tracking framework that ensures consistent global identity assignment across views using trajectory and appearance cues.
On Gradual Semantics for Assumption-Based Argumentation
In computational argumentation, gradual semantics are fine-grained alternatives to extension-based and labelling-based semantics .
LifelongPR: Lifelong knowledge fusion for point cloud place recognition based on replay and prompt learning
Point cloud place recognition (PCPR) plays a crucial role in photogrammetry and robotics applications such as autonomous driving, intelligent transportation, and augmented reality.
Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix
Large language models (LLMs) typically require fine-tuning for domain-specific tasks, and LoRA offers a computationally efficient approach by training low-rank adapters.
IM-LUT: Interpolation Mixing Look-Up Tables for Image Super-Resolution
Super-resolution (SR) has been a pivotal task in image processing, aimed at enhancing image resolution across various applications.
The feed is static: 10 pages of up to 15 cards per stream, rebuilt with the site. Older papers are reachable from task, dataset and method pages and from search. No repository stars are tracked and nothing here is ranked by popularity. Machine-readable twin: JSON.