Best Practice Critic Optimization
Group-based reinforcement learning methods such as GRPO for large language models avoid training a critic by sampling multiple responses for each prompt.
Code that ran · page 9
Papers with a repository link where Syntology ran at least one harvested code sample. 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 121–135 of 5,105 graph papers newer than 2025-07-28 with a Syntology-ran sample; this feed shows the newest 150, newest arXiv id first. Dates and the abstract sentence are from arXiv's metadata (CC0) for 5,105 of 5,105.
Prime Agent: A Self-Improving RLM Harness
Language models are sequential processors, but long-horizon agency requires external information and computation beyond model weights and active context.
ConvergeFlow: Language Flow with Provable Convergence to Token Embeddings
Recent advances in continuous diffusion and flow-based language models (LMs) have achieved performance competitive with discrete LMs.
On the Threat Model of Weird Generalization and Emergent Misalignment
Narrow fine-tuning on small, domain-specific datasets can produce broad and surprising changes in model behavior-a phenomenon called weird generalization (WG).
MetaCaster: Meta-Harness-Optimized Agent for End-to-End Few-Shot Learning of Lightweight Time Series Forecasters
Time series forecasting (TSF) is evolving toward multimodal and agentic settings, yet using foundation models remains uneconomical in resource-constrained scenarios, where compact, specialized forecasters are more…
RAD: Rule-Augmented Relational Anomaly Detection
Anomaly detection is often applied to data stored in relational databases, yet most existing methods require flattening multiple tables into a single feature matrix.
DF-MoE: Generalizable Deepfake Detection via Multimodal Sparse Mixture-of-Experts
Audio-visual deepfake detection is an actively studied topic, where one of the main challenges is to develop detectors able to generalize across deepfake generation methods.
The Geometry of Low-Resource Language Representations
The performance gap between low- and high-resource languages in LLMs is widely known, but it remains unclear which internal model factors drive these disparities.
Hierarchical Exponential-Gaussian Mixtures for Watch-Time Distribution Prediction
Accurate watch-time (WT) prediction is an important requirement for short-video recommendations.
Test-Time Adaptation for ECG Classification via SQI-Gated Self-Training and Beat-Rhythm Consistency
Deep learning models for electrocardiogram (ECG) classification often suffer from significant performance degradation when deployed in unseen domains due to shifts in acquisition devices and patient populations.
ADDA: a Modular Framework for Representing, Simulating and Assimilating Dynamics with End-to-end Differentiability
Data assimilation (DA) is an essential tool for prediction and understanding in the geosciences.
Poisson Subspace Clustering: Focusing on the Essentials in Count Data
Count data represented as a matrix of non-negative integer values, such as contingency tables, are prevalent across diverse domains.
The Laws of Context Allocation: Causal Measurement and Closed-Loop Orchestration in Generative Search
As Retrieval-Augmented Generation (RAG) shifts toward diverse portfolio generation, it is stymied by two critical bottlenecks: flawed measurement of evidence utilization, and suboptimal context budget allocation.
Language Chain in Alignment: Cross-lingual Ranking Preference Optimization
The alignment of Large Language Models heavily relies on English-centric high-quality preference data, which often leads to suboptimal performance in other languages.
PatchWrite: One Line, Not One Section -- Compile-Gated, Validity-Preserving Editing for AI-Drafted Manuscripts
Automated manuscript pipelines often regenerate an entire section to repair a local defect, allowing unrelated metrics and citations to change even when the resulting PDF still builds.
From the archive archive 2025-07-28 — filtered to papers Syntology ran Syntology
Cards 121–135 of 31,700 archive papers with a code link, filtered to those where Syntology ran at least one sample (the archive chip labels the rows, the Syntology chip labels the filter; the count is the archive rows that pass it); this feed shows the newest 150, archive date first (newest archive date 2025-07-17). Within a month, dated rows come first, then the 819 undated rows placed by the month in their arXiv id. 1 archive paper with neither a date nor an arXiv id cannot be placed and is not listed.
OpenUnlearning: Accelerating LLM Unlearning via Unified Benchmarking of Methods and Metrics
Robust unlearning is crucial for safely deploying large language models (LLMs) in environments where data privacy, model safety, and regulatory compliance must be ensured.
BSA: Ball Sparse Attention for Large-scale Geometries
Self-attention scales quadratically with input size, limiting its use for large-scale physical systems.
SSLAM: Enhancing Self-Supervised Models with Audio Mixtures for Polyphonic Soundscapes
Self-supervised pre-trained audio networks have seen widespread adoption in real-world systems, particularly in multi-modal large language models.
TreeRL: LLM Reinforcement Learning with On-Policy Tree Search
Reinforcement learning (RL) with tree search has demonstrated superior performance in traditional reasoning tasks.
Self-supervised Learning of Echocardiographic Video Representations via Online Cluster Distillation
Self-supervised learning (SSL) has achieved major advances in natural images and video understanding, but challenges remain in domains like echocardiography (heart ultrasound) due to subtle anatomical structures,…
ClimateChat: Designing Data and Methods for Instruction Tuning LLMs to Answer Climate Change Queries
As the issue of global climate change becomes increasingly severe, the demand for research in climate science continues to grow.
GLAP: General contrastive audio-text pretraining across domains and languages
Contrastive Language Audio Pretraining (CLAP) is a widely-used method to bridge the gap between audio and text domains.
Improving Group Robustness on Spurious Correlation via Evidential Alignment
Deep neural networks often learn and rely on spurious correlations, i.e., superficial associations between non-causal features and the targets.
Shapley Machine: A Game-Theoretic Framework for N-Agent Ad Hoc Teamwork
Open multi-agent systems are increasingly important in modeling real-world applications, such as smart grids, swarm robotics, etc.
Anti-Aliased 2D Gaussian Splatting
2D Gaussian Splatting (2DGS) has recently emerged as a promising method for novel view synthesis and surface reconstruction, offering better view-consistency and geometric accuracy than volumetric 3DGS.
Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs
In multimodal large language models (MLLMs), the length of input visual tokens is often significantly greater than that of their textual counterparts, leading to a high inference cost.
Probably Approximately Correct Labels
Obtaining high-quality labeled datasets is often costly, requiring either extensive human annotation or expensive experiments.
The Diffusion Duality
Uniform-state discrete diffusion models hold the promise of fast text generation due to their inherent ability to self-correct.
SlotPi: Physics-informed Object-centric Reasoning Models
Understanding and reasoning about dynamics governed by physical laws through visual observation, akin to human capabilities in the real world, poses significant challenges.
ConTextTab: A Semantics-Aware Tabular In-Context Learner
Tabular in-context learning (ICL) has recently achieved state-of-the-art (SOTA) performance on several tabular prediction tasks.
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.