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Audio-DeepThinker: Progressive Reasoning-Aware Reinforcement Learning for High-Quality Chain-of-Thought Emergence in Audio Language Models

arXiv:2604.18187v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) have made significant progress in audio understanding, yet they primarily operate as perception-and-answer systems

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Auditing Support Strategies in LLMs through Grounded Multi-Turn Social Simulation

DGX agent

arXiv:2604.17079v1 Announce Type: new Abstract: When users seek social support from chatbots, they disclose their situation gradually, yet most evaluations of supportive LLMs rely on single-turn, full

model-releasesarxiv-cs-cl

21 Apr 2026

Authenticated Contradictions from Desynchronized Provenance and Watermarking

arXiv:2603.02378v2 Announce Type: replace-cross Abstract: Cryptographic provenance standards such as C2PA and invisible watermarking are positioned as complementary defenses for content authentication

Auto-encoder model for faster generation of effective one-body gravitational waveform approximations

arXiv:2511.12642v2 Announce Type: replace-cross Abstract: Upgrades to current gravitational wave detectors for the next observation run and upcoming third-generation observatories, like the Einstein t

AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction

arXiv:2510.15339v3 Announce Type: replace Abstract: Building effective knowledge graphs (KGs) for Retrieval-Augmented Generation (RAG) is pivotal for advancing question answering (QA) systems. However

safetyarxiv-cs-cl

Automated Classification of Plasma Regions at Mars Using Machine Learning

arXiv:2604.17131v1 Announce Type: cross Abstract: The plasma environment around Mars is highly variable because it is strongly influenced by the solar wind. Accurate identification of plasma regions a

Automated Palynological Analysis System: Integrating Deep Metric Learning and U^{2}-Net Detection in Hinfty bright field microscopy

arXiv:2604.16743v1 Announce Type: new Abstract: Traditional melissopalynology is a time-consuming and subjective process, often taking 4-6 hours per sample. We present an automated, high-throughput mi

Automated Road Crack Localization to Guide Highway Maintenance

arXiv:2601.16737v2 Announce Type: replace Abstract: Highway networks are crucial for economic prosperity. Climate change-induced temperature fluctuations are exacerbating stress on road pavements, res

local-aiarxiv-cs-cv

Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond

arXiv:2408.11338v2 Announce Type: replace-cross Abstract: Large-scale data collection is essential for developing personalized training data, mitigating the shortage of training data, and fine-tuning

Automatic Slide Updating with User-Defined Dynamic Templates and Natural Language Instructions

arXiv:2604.17894v1 Announce Type: new Abstract: Presentation slides are a primary medium for data-driven reporting, yet keeping complex, analytics-style decks up to date remains labor-intensive. Exist

Applications

Automatic Speech Recognition for Documenting Endangered Languages: Case Study of Ikema Miyakoan

arXiv:2603.26248v2 Announce Type: replace Abstract: Language endangerment poses a major challenge to linguistic diversity worldwide, and technological advances have opened new avenues for documentatio

applicationsarxiv-cs-cl

Agents

Autonomous Unmanned Aircraft Systems for Enhanced Search and Rescue of Drowning Swimmers: Image-Based Localization and Mission Simulation

arXiv:2604.18088v1 Announce Type: new Abstract: Drowning is an omnipresent risk associated with any activity on or in the water, and rescuing a drowning person is particularly challenging because of t

agentsarxiv-cs-cv

Autonomous Vehicle Collision Avoidance With Racing Parameterized Deep Reinforcement Learning

arXiv:2604.16702v1 Announce Type: new Abstract: Road traffic accidents are a leading cause of fatalities worldwide. In the US, human error causes 94% of crashes, resulting in excess of 7,000 pedestria

safetyarxiv-cs-ro

Applications

AutoOR: Scalably Post-training LLMs to Autoformalize Operations Research Problems

arXiv:2604.16804v1 Announce Type: new Abstract: Optimization problems are central to decision-making in manufacturing, logistics, scheduling, and other industrial settings. Translating complicated des

applicationsarxiv-cs-lg

AutoPPA: Automated Circuit PPA Optimization via Contrastive Code-based Rule Library Learning

arXiv:2604.18445v1 Announce Type: new Abstract: Performance, power, and area (PPA) optimization is a fundamental task in RTL design, requiring a precise understanding of circuit functionality and the

AutoRubric: Rubric-Based Generative Rewards for Faithful Multimodal Reasoning

arXiv:2510.14738v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have rapidly advanced from perception tasks to complex multi-step reasoning, yet reinforcement learning wit

researcharxiv-cs-cl

Agents

AutoVQA-G: Self-Improving Agentic Framework for Automated Visual Question Answering and Grounding Annotation

arXiv:2604.17488v1 Announce Type: new Abstract: Manual annotation of high-quality visual question answering with grounding (VQA-G) datasets, which pair visual questions with evidential grounding, is c

agentsarxiv-cs-cv

AvatarPointillist: AutoRegressive 4D Gaussian Avatarization

arXiv:2604.04787v2 Announce Type: replace Abstract: We introduce AvatarPointillist, a novel framework for generating dynamic 4D Gaussian avatars from a single portrait image. At the core of our method

AVRT: Audio-Visual Reasoning Transfer through Single-Modality Teachers

model-releasesarxiv-cs-cv

arXiv:2604.16617v1 Announce Type: new Abstract: Recent advances in reasoning models have shown remarkable progress in text-based domains, but transferring those capabilities to multimodal settings, e.

AWPD: Frequency Shield Network for Agnostic Watermark Presence Detection

model-releasesarxiv-cs-cv

arXiv:2603.06723v3 Announce Type: replace Abstract: Invisible watermarks, as an essential technology for image copyright protection, have been widely deployed with the rapid development of social medi

b8864

b8864 is a build release of llama.cpp, an open-source C/C++ library for large language model inference. The project uses rapid release cycles with frequent build tags published as intermediate develop

b8869

Release b8869 is a version update for llama.cpp, a C/C++ library for LLM inference . This is one of many rapid incremental releases in the llama.cpp project's development cycle, following the pattern

b8870

b8870 is a release from llama.cpp, a project for LLM inference in C/C++ . This release represents a commit snapshot in the rapidly-developed open-source project that enables efficient inference of lar

b8871

B8871 is a build release of llama.cpp, an open-source C/C++ implementation for LLM inference. Build releases in the llama.cpp project use alphanumeric identifiers and represent incremental development

b8872

b8872 is a release tag from llama.cpp, a project that enables LLM inference in C/C++ . The release represents a specific commit or version update to the llama.cpp codebase. Without access to the speci

b8874

b8874 is a release from llama.cpp, a C/C++ library for LLM inference. The llama.cpp project publishes multiple releases in a single day, and b8874 represents an intermediate build version containing u

b8875

B8875 is a release of llama.cpp, a C/C++ implementation for LLM inference . The llama.cpp project does not follow traditional release practices, with multiple releases published in a single day . This

Back into Plato's Cave: Examining Cross-modal Representational Convergence at Scale

arXiv:2604.18572v1 Announce Type: new Abstract: The Platonic Representation Hypothesis suggests that neural networks trained on different modalities (e.g., text and images) align and eventually conver

safetyarxiv-cs-cv

Back to Repair: A Minimal Denoising Network for Time Series Anomaly Detection

arXiv:2604.17388v1 Announce Type: new Abstract: We introduce JuRe (Just Repair), a minimal denoising network for time series anomaly detection that exposes a central finding: architectural complexity

Balance-Guided Sparse Identification of Multiscale Nonlinear PDEs with Small-coefficient Terms

arXiv:2604.18414v1 Announce Type: new Abstract: Data-driven discovery of governing equations has advanced significantly in recent years; however, existing methods often struggle in multiscale systems

Balanced Co-Clustering of Users and Items for Embedding Table Compression in Recommender Systems

arXiv:2604.18351v1 Announce Type: cross Abstract: Recommender systems have advanced markedly over the past decade by transforming each user/item into a dense embedding vector with deep learning models

BARD: Bridging AutoRegressive and Diffusion Vision-Language Models Via Highly Efficient Progressive Block Merging and Stage-Wise Distillation

arXiv:2604.16514v1 Announce Type: new Abstract: Autoregressive vision-language models (VLMs) deliver strong multimodal capability, but their token-by-token decoding imposes a fundamental inference bot

Barrier-enforced multi-objective optimization for direct point and sharp interval forecasting

arXiv:2604.18492v1 Announce Type: new Abstract: This paper proposes a multi-step probabilistic forecasting framework using a single neural-network based model to generate simultaneous point and interv

Applications

BASIL: Bayesian Assessment of Sycophancy in LLMs

arXiv:2508.16846v5 Announce Type: replace-cross Abstract: Sycophancy (overly agreeable or flattering behavior) poses a fundamental challenge for human-AI collaboration, particularly in high-stakes dec

applicationsarxiv-cs-cl

BASIS: Balanced Activation Sketching with Invariant Scalars for 'Ghost Backpropagation'

arXiv:2604.16324v1 Announce Type: new Abstract: The activation memory required for exact backpropagation scales linearly with network depth, context length, and feature dimensionality, forming an O(L

safetyarxiv-cs-lg

BasketHAR: A Multimodal Dataset for Human Activity Recognition and Sport Analysis in Basketball Training Scenarios

model-releasesarxiv-cs-cv

arXiv:2604.17065v1 Announce Type: new Abstract: Human Activity Recognition (HAR) involves the automatic identification of user activities and has gained significant research interest due to its broad

Batch-Adaptive Causal Annotations

arXiv:2502.10605v3 Announce Type: replace-cross Abstract: Estimating the causal effects of interventions is crucial to policy and decision-making, yet outcome data are often missing or subject to non-

safetyarxiv-cs-lg

Bayesian Neural Networks: An Introduction and Survey

arXiv:2006.12024v3 Announce Type: replace-cross Abstract: Neural Networks (NNs) have provided state-of-the-art results for many challenging machine learning tasks such as detection, regression and cla

> be Yann LeCun > spend years building JEPA at Meta > company focuses on LLaMA instead > his idea stays complicated and unused > robotics pl…

model-releasesyann-lecun--x

> be Yann LeCun > spend years building JEPA at Meta > company focuses on LLaMA instead > his idea stays complicated and unused > robotics plans get dropped > decides to leave and start AMI Labs > buil

Beam-Plasma Collective Oscillations in Intense Charged-Particle Beams: Dielectric Response Theory, Langmuir Wave Dispersion, and Unsupervised Detection via Prometheus

arXiv:2603.10457v3 Announce Type: replace-cross Abstract: We develop a theoretical and computational framework for beam-plasma collective oscillations in intense charged-particle beams at intermediate

Before You Interpret the Profile: Validity Scaling for LLM Metacognitive Self-Report

arXiv:2604.17707v1 Announce Type: new Abstract: Clinical personality assessment screens response validity before interpreting substantive scales. LLM evaluation does not. We apply the validity scaling

researcharxiv-cs-cl

BEFT: Bias-Efficient Fine-Tuning of Language Models in Low-Data Regimes

arXiv:2509.15974v2 Announce Type: replace Abstract: Fine-tuning the bias terms of large language models (LLMs) has the potential to achieve unprecedented parameter efficiency while maintaining competi

BenchMarker: An Education-Inspired Toolkit for Highlighting Flaws in Multiple-Choice Benchmarks

arXiv:2602.06221v2 Announce Type: replace Abstract: Multiple-choice question answering (MCQA) is standard in NLP, but benchmarks lack rigorous quality control. We present BenchMarker, an education-ins

Benchmarking programs?

The Reddit post 'Benchmarking programs?' in r/ollama likely discusses tools and methods for measuring the performance of local language models running on Ollama. Available benchmarking tools for Ollam

local-air-ollama

Benchmarking Real-Time Question Answering via Executable Code Workflows

arXiv:2604.16349v1 Announce Type: cross Abstract: Retrieving real-time information is a fundamental capability for search-integrated agents in real-world applications. However, existing benchmarks are

Benchmarking System Dynamics AI Assistants: Cloud Versus Local LLMs on CLD Extraction and Discussion

arXiv:2604.18566v1 Announce Type: cross Abstract: We present a systematic evaluation of large language model families -- spanning both proprietary cloud APIs and locally-hosted open-source models -- o

BengaliMoralBench: A Benchmark for Auditing Moral Reasoning in Large Language Models within Bengali Language and Culture

arXiv:2511.03180v2 Announce Type: replace Abstract: As multilingual Large Language Models (LLMs) gain traction across South Asia, their alignment with local ethical norms, particularly for Bengali, sp

Better with Less: Tackling Heterogeneous Multi-Modal Image Joint Pretraining via Conditioned and Degraded Masked Autoencoder

arXiv:2604.16952v1 Announce Type: new Abstract: Learning robust representations across extremely heterogeneous modalities remains a fundamental challenge in multi-modal vision. As a critical and profo

safetyarxiv-cs-cv