Trending research and the full catalog - each paper linked to the benchmarks, methods, and models it introduces.
Filtering here covers the 2,000 most recent papers, as much as one page can hold in memory. See the full index of 22,094 papers.
1 May 2026
Dynamic link prediction is important for modeling evolving interactions in social, communication, financial, and transportation networks. Classical temporal graph models capture changes over time, but they may struggle to represent rapidly evolving node-edge interactions in…
1 May 2026
Quantization is an effective strategy to reduce the storage and computation footprint of large language models (LLMs). Post-training quantization (PTQ) is a leading approach for compressing LLMs.
1 May 2026
Automatic heuristic design (AHD) has emerged as a promising paradigm for solving NP-hard combinatorial optimization problems (COPs). Recent works show that large language models (LLMs), when integrated into well-designed frameworks (i.e., LLM-AHD), can autonomously discover…
1 May 2026
We present swarm-attack, an open-source adversarial testing framework in which multiple lightweight LLM agents coordinate through shared memory, parallel exploration, and evolutionary optimization.
1 May 2026
Coding and computation remain major bottlenecks in Markov chain Monte Carlo (MCMC) workflows, especially as modern sampling algorithms have become increasingly complex and existing probabilistic programming systems remain limited in model support, extensibility, and…
1 May 2026
Modern deep learning commonly relies on AdamW with prescribed learning rate schedules, but recent works challenge both components: Schedule-Free optimization removes explicit schedules via iterate averaging, and Muon improves the update geometry by orthogonalizing momentum for…
1 May 2026
Estimating an $N \times N$ quantum kernel from circuit fidelities requires $Θ(N^2 S)$ measurement shots, the dominant bottleneck for deployment on near-term hardware. Existing budget-saving methods (Nyström-QKE, ShoFaR, kernel-target alignment) sub-sample \emph{which} entries to…
1 May 2026
Automated program repair at repository scale requires an agent to locate a fault among thousands of files and synthesize a correct patch. Existing graph-based agents represent how a repository is organized into files, classes, and functions, but they do not model how variable…
1 May 2026
As autonomous agents (e.g., OpenClaw) increasingly operate with deep system-level privileges to execute complex tasks, they introduce severe, unmitigated security risks.
23 Apr 2026
This paper aims to synthesize current knowledge on generative AI in IT project management using the PRISMA methodology to provide researchers with a comprehensive perspective on techniques, applications, adoption trends, limitations, and integration across project management…
Jian Yang, Ruibin Yuan, Yizhi Li · 21 Apr 2026
TACO is a self-evolving compression framework that automatically discovers and refines compression rules from interaction trajectories to improve long-horizon agent performance while reducing token overhead.
Yu Wang, Xunliang Cai, Yuxin Chen · 20 Apr 2026
As reinforcement learning continues to scale the training of large language model-based agents, reliably verifying agent behaviors in complex environments has become increasingly challenging.
Mingqiao Ye, Afshin Dehghan, Roman Bachmann · 16 Apr 2026
Tokenization is a key component of autoregressive (AR) generative models, converting raw data into more manageable units for modeling.
14 Apr 2026
With the growing adoption of AI systems, reasoning about how society can exert control over AI becomes an increasingly urgent problem. Existing work on democratic control largely focuses on macro-level governance.
Stefan Schulz, Fernando Edelstein, Hannah Dröge · 13 Apr 2026
Real-time free-viewpoint rendering requires balancing multi-camera redundancy with the latency constraints of interactive applications.
Eslam Reda, Sara El-Metwally · 13 Apr 2026
Large Language Models have demonstrated remarkable capabilities in generating contextually relevant and grammatically correct text.
Xiaodong Yang, Meng'en Qin, Yu Song · 11 Apr 2026
A3-FPN enhances multi-scale feature representation through asymptotically disentangled framework and content-aware attention modules, improving small object recognition and dense prediction tasks.
10 Apr 2026
Topic modeling is a branch of Natural Language Processing (NLP) that aims to organize large collections of texts into coherent groups according to word co-occurrence patterns, with Latent Dirichlet Allocation (LDA) remaining one of the most widely used and interpretable…
7 Apr 2026
Constructing artificial lexicons that are pronounceable, typologically plausible, and semantically structured remains an open challenge in computational linguistics. Existing conlang generators either lack formal phonotactic guarantees or delegate generation to opaque,…
Qihang Yu, Ju He, Liang-Chieh Chen · 6 Apr 2026
Anticipating diverse future states is a central challenge in video world modeling.
Ziwei Liu, Jingkang Yang, Shulin Tian · 2 Apr 2026
Recent streaming video understanding methods increasingly rely on complex memory mechanisms to handle long video streams.
1 Apr 2026
Supervised fine-tuning (SFT) is a common first stage of LLM post-training, teaching the model to follow instructions and shaping its behavior as a helpful assistant. At the same time, SFT may harm the fundamental capabilities of an LLM, particularly after long pretraining: a…
1 Apr 2026
Prompt optimization improves language models without updating their weights by searching for a better system prompt, but its effectiveness varies widely across tasks. We study what makes a task amenable to prompt optimization.
1 Apr 2026
Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to autoregressive generation by enabling parallel token prediction. However, practical dLLM decoding still suffers from high inference latency, which limits deployment.