Search: “inference”

arXiv:2510.14420v4 Announce Type: replace-cross Abstract: Language models often struggle to follow multi-constraint instructions that are crucial for real-world applications. Existing reinforcement le

agentsarxiv-cs-ai

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Model Releases

KG-Hopper: Empowering Compact Open LLMs with Knowledge Graph Reasoning via Reinforcement Learning

DGX agent

arXiv:2603.21440v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) demonstrate impressive natural language capabilities but often struggle with knowledge-intensive reasoning tasks.

model-releasesarxiv-cs-ai

15 Apr 2026

KnowRL: Boosting LLM Reasoning via Reinforcement Learning with Minimal-Sufficient Knowledge Guidance

arXiv:2604.12627v1 Announce Type: new Abstract: RLVR improves reasoning in large language models, but its effectiveness is often limited by severe reward sparsity on hard problems. Recent hint-based R

Latent patterns of urban mixing in mobility analysis across five global cities

arXiv:2604.12202v1 Announce Type: new Abstract: This study leverages large-scale travel surveys for over 200,000 residents across Boston, Chicago, Hong Kong, London, and Sao Paulo. With rich individua

Lightning OPD: Efficient Post-Training for Large Reasoning Models with Offline On-Policy Distillation

arXiv:2604.13010v1 Announce Type: cross Abstract: On-policy distillation (OPD) has emerged as an efficient post-training paradigm for large language models. However, standard OPD requires a live teach

Tutorials

LLM-Guided Semantic Bootstrapping for Interpretable Text Classification with Tsetlin Machines

arXiv:2604.12223v1 Announce Type: cross Abstract: Pretrained language models (PLMs) like BERT provide strong semantic representations but are costly and opaque, while symbolic models such as the Tsetl

tutorialsarxiv-cs-ai

Applications

LLM-HYPER: Generative CTR Modeling for Cold-Start Ad Personalization via LLM-Based Hypernetworks

arXiv:2604.12096v1 Announce Type: new Abstract: On online advertising platforms, newly introduced promotional ads face the cold-start problem, as they lack sufficient user feedback for model training.

applicationsarxiv-cs-ai

MAML-KT: Addressing Cold Start Problem in Knowledge Tracing for New Students via Few-Shot Model-Agnostic Meta Learning

arXiv:2603.00137v2 Announce Type: replace-cross Abstract: Knowledge tracing (KT) models are commonly evaluated by training on early interactions from all students and testing on later responses. While

Meet Dynamic Individual Preferences: Resolving Conflicting Human Value with Paired Fine-Tuning

arXiv:2604.12479v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have significantly improved the alignment of models with general human preferences. However, a major cha

safetyarxiv-cs-cl

MISID: A Multimodal Multi-turn Dataset for Complex Intent Recognition in Strategic Deception Games

arXiv:2604.12700v1 Announce Type: new Abstract: Understanding human intent in complex multi-turn interactions remains a fundamental challenge in human-computer interaction and behavioral analysis. Whi

Models Know Their Shortcuts: Deployment-Time Shortcut Mitigation

arXiv:2604.12277v1 Announce Type: new Abstract: Pretrained language models often rely on superficial features that appear predictive during training yet fail to generalize at test time, a phenomenon k

safetyarxiv-cs-lg

MoshiRAG: Asynchronous Knowledge Retrieval for Full-Duplex Speech Language Models

model-releasesarxiv-cs-cl

arXiv:2604.12928v1 Announce Type: new Abstract: Speech-to-speech language models have recently emerged to enhance the naturalness of conversational AI. In particular, full-duplex models are distinguis

One View Is Enough! Monocular Training for In-the-Wild Novel View Generation

arXiv:2603.23488v2 Announce Type: replace Abstract: Monocular novel-view synthesis has long required multi-view image pairs for supervision, limiting training data scale and diversity. We argue it is

Applications

PDF-GS: Progressive Distractor Filtering for Robust 3D Gaussian Splatting

arXiv:2604.12580v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting (3DGS) have enabled impressive real-time photorealistic rendering. However, conventional training pipelines inh

applicationsarxiv-cs-cv

Applications

Pi-HOC: Pairwise 3D Human-Object Contact Estimation

arXiv:2604.12923v1 Announce Type: new Abstract: Resolving real-world human-object interactions in images is a many-to-many challenge, in which disentangling fine-grained concurrent physical contact is

applicationsarxiv-cs-cv

PILOT: Planning via Internalized Latent Optimization Trajectories for Large Language Models

arXiv:2601.19917v2 Announce Type: replace Abstract: Strategic planning is critical for multi-step reasoning, yet compact Large Language Models (LLMs) often lack the capacity to formulate global strate

researcharxiv-cs-cl

Polynomial Expansion Rank Adaptation: Enhancing Low-Rank Fine-Tuning with High-Order Interactions

arXiv:2604.11841v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) is a widely used strategy for efficient fine-tuning of large language models (LLMs), but its strictly linear structure fund

PromptEcho: Annotation-Free Reward from Vision-Language Models for Text-to-Image Reinforcement Learning

arXiv:2604.12652v1 Announce Type: cross Abstract: Reinforcement learning (RL) can improve the prompt following capability of text-to-image (T2I) models, yet obtaining high-quality reward signals remai

Rapid LoRA Aggregation for Wireless Channel Adaptation in Open-Set Radio Frequency Fingerprinting

arXiv:2604.12834v1 Announce Type: cross Abstract: Radio frequency fingerprints (RFFs) enable secure wireless authentication but struggle in open-set scenarios with unknown devices and varying channels

ReflectCAP: Detailed Image Captioning with Reflective Memory

arXiv:2604.12357v1 Announce Type: new Abstract: Detailed image captioning demands both factual grounding and fine-grained coverage, yet existing methods have struggled to achieve them simultaneously.

RePAIR: Interactive Machine Unlearning through Prompt-Aware Model Repair

arXiv:2604.12820v1 Announce Type: new Abstract: Large language models (LLMs) inherently absorb harmful knowledge, misinformation, and personal data during pretraining on large-scale web corpora, with

local-aiarxiv-cs-ai

Robust Explanations for User Trust in Enterprise NLP Systems

arXiv:2604.12069v1 Announce Type: cross Abstract: Robust explanations are increasingly required for user trust in enterprise NLP, yet pre-deployment validation is difficult in the common case of black

Safety Training Modulates Harmful Misalignment Under On-Policy RL, But Direction Depends on Environment Design

arXiv:2604.12500v1 Announce Type: new Abstract: Specification gaming under Reinforcement Learning (RL) is known to cause LLMs to develop sycophantic, manipulative, or deceptive behavior, yet the condi

safetyarxiv-cs-lg

SceneCritic: A Symbolic Evaluator for 3D Indoor Scene Synthesis

arXiv:2604.13035v1 Announce Type: cross Abstract: Large Language Models (LLMs) and Vision-Language Models (VLMs) increasingly generate indoor scenes through intermediate structures such as layouts and

researcharxiv-cs-cl

Simulation as Supervision: Mechanistic Pretraining for Scientific Discovery

arXiv:2507.08977v4 Announce Type: replace-cross Abstract: Scientific modeling faces a tradeoff between the interpretability of mechanistic theory and the predictive power of machine learning. While ex

SinkSAM-Net: Knowledge-Driven Self-Supervised Sinkhole Segmentation Using Topographic Priors and Segment Anything Model

model-releasesarxiv-cs-cv

arXiv:2410.01473v2 Announce Type: replace Abstract: Soil sinkholes significantly influence soil degradation, infrastructure vulnerability, and landscape evolution. However, their irregular shapes, com

SOAR: Self-Correction for Optimal Alignment and Refinement in Diffusion Models

arXiv:2604.12617v1 Announce Type: cross Abstract: The post-training pipeline for diffusion models currently has two stages: supervised fine-tuning (SFT) on curated data and reinforcement learning (RL)

TCL: Enabling Fast and Efficient Cross-Hardware Tensor Program Optimization via Continual Learning

model-releasesarxiv-cs-lg

arXiv:2604.12891v1 Announce Type: new Abstract: Deep learning (DL) compilers rely on cost models and auto-tuning to optimize tensor programs for target hardware. However, existing approaches depend on

The Non-Optimality of Scientific Knowledge: Path Dependence, Lock-In, and The Local Minimum Trap

arXiv:2604.11828v1 Announce Type: new Abstract: Science is widely regarded as humanity's most reliable method for uncovering truths about the natural world. Yet the trajectory of scientific discovery

Think Through Uncertainty: Improving Long-Form Generation Factuality via Reasoning Calibration

arXiv:2604.12046v1 Announce Type: new Abstract: Large language models (LLMs) often hallucinate in long-form generation. Existing approaches mainly improve factuality through post-hoc revision or reinf

researcharxiv-cs-cl

Time-reversed Flow Matching with Worst Transport in High-dimensional Latent Space for Image Anomaly Detection

arXiv:2508.05461v3 Announce Type: replace Abstract: Likelihood-based deep generative models have been widely investigated for Image Anomaly Detection (IAD), particularly Normalizing Flows, yet their s

local-aiarxiv-cs-cv

Tutorials

TimeSAF: Towards LLM-Guided Semantic Asynchronous Fusion for Time Series Forecasting

arXiv:2604.12648v1 Announce Type: cross Abstract: Despite the recent success of large language models (LLMs) in time-series forecasting, most existing methods still adopt a Deep Synchronous Fusion str

tutorialsarxiv-cs-ai

Toward Efficient and Robust Behavior Models for Multi-Agent Driving Simulation

arXiv:2512.05812v5 Announce Type: replace-cross Abstract: Scalable multi-agent driving simulation requires behavior models that are both realistic and computationally efficient. We address this by opt

local-aiarxiv-cs-cv

Towards Realistic and Consistent Orbital Video Generation via 3D Foundation Priors

arXiv:2604.12309v1 Announce Type: new Abstract: We present a novel method for generating geometrically realistic and consistent orbital videos from a single image of an object. Existing video generati

ToxiTrace: Gradient-Aligned Training for Explainable Chinese Toxicity Detection

model-releasesarxiv-cs-cl

arXiv:2604.12321v1 Announce Type: new Abstract: Existing Chinese toxic content detection methods mainly target sentence-level classification but often fail to provide readable and contiguous toxic evi

Training single-electron and single-photon stochastic physical neural networks

arXiv:2604.10861v1 Announce Type: cross Abstract: The computational demands of deep learning motivate the investigation of alternative approaches to computation. One alternative is physical neural net

Tutorials

Ultra-low-light computer vision using trained photon correlations

arXiv:2604.11993v1 Announce Type: new Abstract: Illumination using correlated photon sources has been established as an approach to allowing high-fidelity images to be reconstructed from noisy camera

tutorialsarxiv-cs-cv

Uncertainty Quantification in CNN Through the Bootstrap of Convex Neural Networks

arXiv:2604.11833v1 Announce Type: new Abstract: Despite the popularity of Convolutional Neural Networks (CNN), the problem of uncertainty quantification (UQ) of CNN has been largely overlooked. Lack o

Variational Autoencoding Discrete Diffusion with Enhanced Dimensional Correlations Modeling

arXiv:2505.17384v2 Announce Type: replace-cross Abstract: Discrete diffusion models have recently shown great promise for modeling complex discrete data, with masked diffusion models (MDMs) offering a

Hardware

VFA: Relieving Vector Operations in Flash Attention with Global Maximum Pre-computation

arXiv:2604.12798v1 Announce Type: cross Abstract: FlashAttention-style online softmax enables exact attention computation with linear memory by streaming score tiles through on-chip memory and maintai

hardwarearxiv-cs-ai

VidTAG: Temporally Aligned Video to GPS Geolocalization with Denoising Sequence Prediction at a Global Scale

arXiv:2604.12159v1 Announce Type: new Abstract: The task of video geolocalization aims to determine the precise GPS coordinates of a video's origin and map its trajectory; with applications in forensi

VPTracker: Global Vision-Language Tracking via Visual Prompt

arXiv:2512.22799v2 Announce Type: replace Abstract: Vision-Language Tracking aims to continuously localize objects described by a visual template and a language description. Existing methods, however,

local-aiarxiv-cs-cv

Agents

WebFactory: Automated Compression of Foundational Language Intelligence into Grounded Web Agents

arXiv:2603.05044v2 Announce Type: replace Abstract: Current paradigms for training GUI agents are fundamentally limited by a reliance on either unsafe, non-reproducible live web interactions or costly

agentsarxiv-cs-ai

A Benchmark for Gap and Overlap Analysis as a Test of KG Task Readiness

arXiv:2604.10853v1 Announce Type: new Abstract: Task-oriented evaluation of knowledge graph (KG) quality increasingly asks whether an ontology-based representation can answer the competency questions

A Compact and Efficient 1.251 Million Parameter Machine Learning CNN Model PD36-C for Plant Disease Detection: A Case Study

arXiv:2604.11332v1 Announce Type: cross Abstract: Deep learning has markedly advanced image based plant disease diagnosis as improved hardware and dataset quality have enabled increasingly accurate ne

A Metamorphic Testing Perspective on Knowledge Distillation for Language Models of Code: Does the Student Deeply Mimic the Teacher?

arXiv:2511.05476v4 Announce Type: replace-cross Abstract: Transformer-based language models of code have achieved state-of-the-art performance across a wide range of software analytics tasks, but thei

A molecular clock for writing systems reveals the quantitative impact of imperial power on cultural evolution

arXiv:2604.10957v1 Announce Type: cross Abstract: Writing systems are cultural replicators whose evolution has never been studied quantitatively at global scale. We compile the Global Script Database

A Proposed Biomedical Data Policy Framework to Reduce Fragmentation, Improve Quality, and Incentivize Sharing in Indian Healthcare in the era of Artificial Intelligence and Digital Health

arXiv:2604.11125v1 Announce Type: new Abstract: India generates vast biomedical data through postgraduate research, government hospital services and audits, government schemes, private hospitals and t