Newest with code · page 3
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 31–45 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 31–45 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).
InstructFLIP: Exploring Unified Vision-Language Model for Face Anti-spoofing
Face anti-spoofing (FAS) aims to construct a robust system that can withstand diverse attacks.
Simplifications are Absolutists: How Simplified Language Reduces Word Sense Awareness in LLM-Generated Definitions
Large Language Models (LLMs) can provide accurate word definitions and explanations for any context.
DAC: A Dynamic Attention-aware Approach for Task-Agnostic Prompt Compression
Task-agnostic prompt compression leverages the redundancy in natural language to reduce computational overhead and enhance information density within prompts, especially in long-context scenarios.
Choosing the Better Bandit Algorithm under Data Sharing: When Do A/B Experiments Work?
We study A/B experiments that are designed to compare the performance of two recommendation algorithms.
Analytic estimation of parameters of stochastic volatility diffusion models with exponential-affine characteristic function for currency option pricing
This dissertation develops and justifies a novel method for deriving approximate formulas to estimate two parameters in stochastic volatility diffusion models with exponentially-affine characteristic functions and…
Arctic Inference with Shift Parallelism: Fast and Efficient Open Source Inference System for Enterprise AI
Inference is now the dominant AI workload, yet existing systems force trade-offs between latency, throughput, and cost.
AI Wizards at CheckThat! 2025: Enhancing Transformer-Based Embeddings with Sentiment for Subjectivity Detection in News Articles
This paper presents AI Wizards' participation in the CLEF 2025 CheckThat!
Beyond Task-Specific Reasoning: A Unified Conditional Generative Framework for Abstract Visual Reasoning
Abstract visual reasoning (AVR) enables humans to quickly discover and generalize abstract rules to new scenarios.
PGT-I: Scaling Spatiotemporal GNNs with Memory-Efficient Distributed Training
Spatiotemporal graph neural networks (ST-GNNs) are powerful tools for modeling spatial and temporal data dependencies.
Are Vision Foundation Models Ready for Out-of-the-Box Medical Image Registration?
Foundation models, pre-trained on large image datasets and capable of capturing rich feature representations, have recently shown potential for zero-shot image registration.
Streaming 4D Visual Geometry Transformer
Perceiving and reconstructing 4D spatial-temporal geometry from videos is a fundamental yet challenging computer vision task.
CharaConsist: Fine-Grained Consistent Character Generation
In text-to-image generation, producing a series of consistent contents that preserve the same identity is highly valuable for real-world applications.
Langevin Flows for Modeling Neural Latent Dynamics
Neural populations exhibit latent dynamical structures that drive time-evolving spiking activities, motivating the search for models that capture both intrinsic network dynamics and external unobserved influences.
DrafterBench: Benchmarking Large Language Models for Tasks Automation in Civil Engineering
Large Language Model (LLM) agents have shown great potential for solving real-world problems and promise to be a solution for tasks automation in industry.
Precision Spatio-Temporal Feature Fusion for Robust Remote Sensing Change Detection
Remote sensing change detection is vital for monitoring environmental and urban transformations but faces challenges like manual feature extraction and sensitivity to noise.
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.