Search: “inference”

arXiv:2412.01782v4 Announce Type: replace-cross Abstract: DETR and its variants have emerged as promising architectures for object detection, offering an end-to-end prediction pipeline. In practice, h

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Model Releases

VecHeart: Holistic Four-Chamber Cardiac Anatomy Modeling via Hybrid VecSets

DGX agent

arXiv:2604.19403v1 Announce Type: new Abstract: Accurate cardiac anatomy modeling requires the model to be able to handle intricate interrelations among structures. In this paper, we propose VecHeart,

model-releasesarxiv-cs-cv

22 Apr 2026

VIGIL: An Extensible System for Real-Time Detection and Mitigation of Cognitive Bias Triggers

arXiv:2604.03261v2 Announce Type: replace Abstract: The rise of generative AI is posing increasing risks to online information integrity and civic discourse. Most concretely, such risks can materialis

safetyarxiv-cs-cl

VISTA: Verification In Sequential Turn-based Assessment

arXiv:2510.27052v5 Announce Type: replace Abstract: Hallucination--defined here as generating statements unsupported or contradicted by available evidence or conversational context--remains a major ob

Watch the Weights: Unsupervised monitoring and control of fine-tuned LLMs

arXiv:2508.00161v3 Announce Type: replace-cross Abstract: The releases of powerful open-weight large language models (LLMs) are often not accompanied by access to their full training data. Existing in

Agents

WebUncertainty: Dual-Level Uncertainty Driven Planning and Reasoning For Autonomous Web Agent

arXiv:2604.17821v2 Announce Type: replace Abstract: Recent advancements in large language models (LLMs) have empowered autonomous web agents to execute natural language instructions directly on real-w

agentsarxiv-cs-ai

When Does Verification Pay Off? A Closer Look at LLMs as Solution Verifiers

arXiv:2512.02304v2 Announce Type: replace Abstract: Large language models (LLMs) can act as both problem solvers and solution verifiers, where the latter select high-quality answers from a pool of sol

Local Ai

A Lightweight Transformer for Pain Recognition from Brain Activity

arXiv:2604.16491v1 Announce Type: new Abstract: Pain is a multifaceted and widespread phenomenon with substantial clinical and societal burden, making reliable automated assessment a critical objectiv

local-aiarxiv-cs-cv

A Model and Estimation of the Bitcoin Transaction Fee

arXiv:2604.17183v1 Announce Type: cross Abstract: Bitcoin transaction fees will become more important as the block subsidy declines, but fee formation is hard to study with blockchain data alone becau

A Probabilistic Consensus-Driven Approach for Robust Counterfactual Explanations

arXiv:2604.17494v1 Announce Type: new Abstract: Counterfactual explanations (CFEs) are essential for interpreting black-box models, yet they often become invalid when models are slightly changed. Exis

A Systematic Survey and Benchmark of Deep Learning for Molecular Property Prediction in the Foundation Model Era

arXiv:2604.16586v1 Announce Type: new Abstract: Molecular property prediction integrates quantum chemistry, cheminformatics, and deep learning to connect molecular structure with physicochemical and b

Adaptive Local Frequency Filtering for Fourier-Encoded Implicit Neural Representations

arXiv:2604.02846v2 Announce Type: replace Abstract: Fourier-encoded implicit neural representations (INRs) have shown strong capability in modeling continuous signals from discrete samples. However, c

Local Ai

Aligning Language Models with Real-time Knowledge Editing

arXiv:2508.01302v3 Announce Type: replace Abstract: Knowledge editing aims to modify outdated knowledge in language models efficiently while retaining their original capabilities. Mainstream datasets

local-aiarxiv-cs-cl

Amortized Inverse Kinematics via Graph Attention for Real-Time Human Avatar Animation

arXiv:2604.16629v1 Announce Type: new Abstract: Inverse kinematics (IK) is a core operation in animation, robotics, and biomechanics: given Cartesian constraints, recover joint rotations under a known

An Integrated Deep-Learning Framework for Peptide-Protein Interaction Prediction and Target-Conditioned Peptide Generation with ConGA-PePPI and TC-PepGen

arXiv:2604.18467v1 Announce Type: new Abstract: Motivation: Peptide-protein interactions (PepPIs) are central to cellular regulation and peptide therapeutics, but experimental characterization remains

Hardware

AQPIM: Breaking the PIM Capacity Wall for LLMs with In-Memory Activation Quantization

arXiv:2604.18137v1 Announce Type: cross Abstract: Processing-in-Memory (PIM) architectures offer a promising solution to the memory bottlenecks in data-intensive machine learning, yet often overlook t

hardwarearxiv-cs-lg

ARCS: Autoregressive Circuit Synthesis with Topology-Aware Graph Attention and Spec Conditioning

arXiv:2603.29068v3 Announce Type: replace Abstract: This paper presents ARCS (Autoregressive Circuit Synthesis), a system for amortized analog circuit generation. ARCS produces complete, SPICE-simulat

safetyarxiv-cs-lg

Applications

Are they lovers or friends? Evaluating LLMs' Social Reasoning in English and Korean Dialogues

arXiv:2510.19028v3 Announce Type: replace Abstract: As LLMs are increasingly deployed in real-world interactions, their social reasoning in interpersonal communication becomes critical. To explore the

applicationsarxiv-cs-cl

Tutorials

Argument Reconstruction as Supervision for Critical Thinking in LLMs

arXiv:2603.17432v2 Announce Type: replace Abstract: To think critically about arguments, human learners are trained to identify, reconstruct, and evaluate arguments. Argument reconstruction is especia

tutorialsarxiv-cs-cl

Attention-ResUNet for Automated Fetal Head Segmentation

arXiv:2604.18148v1 Announce Type: new Abstract: Automated fetal head segmentation in ultrasound images is critical for accurate biometric measurements in prenatal care. While existing deep learning ap

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

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

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

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

BioVLM: Routing Prompts, Not Parameters, for Cross-Modality Generalization in Biomedical VLMs

arXiv:2604.17629v1 Announce Type: new Abstract: Pretrained biomedical vision-language models (VLMs) such as BioMedCLIP perform well on average but often degrade on challenging modalities where inter-c

Bounded Graph Clustering with Graph Neural Networks

arXiv:2512.05623v2 Announce Type: replace Abstract: In community detection, many methods require the user to specify the number of clusters in advance since an exhaustive search over all possible valu

Can Explicit Physical Feasibility Benefit VLA Learning? An Empirical Study

arXiv:2604.17896v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models map multimodal inputs directly to robot actions and are typically trained through large-scale imitation learning. Wh

safetyarxiv-cs-lg

CARI4D: Category Agnostic 4D Reconstruction of Human-Object Interaction

arXiv:2512.11988v3 Announce Type: replace Abstract: Accurate capture of human-object interaction from ubiquitous sensors like RGB cameras is important for applications in human understanding, gaming,

Channel Attention-Guided Cross-Modal Knowledge Distillation for Referring Image Segmentation

arXiv:2604.16806v1 Announce Type: new Abstract: Referring image segmentation (RIS) requires accurate segmentation of target regions in images according to language descriptions, which is a cross-modal

CoDial: Interpretable Task-Oriented Dialogue Systems Through Dialogue Flow Alignment

arXiv:2506.02264v3 Announce Type: replace Abstract: Building Task-Oriented Dialogue (TOD) systems that generalize across different tasks remains a challenging problem. Data-driven approaches often str

ConforNets: Latents-Based Conformational Control in OpenFold3

arXiv:2604.18559v1 Announce Type: cross Abstract: Models from the AlphaFold (AF) family reliably predict one dominant conformation for most well-ordered proteins but struggle to capture biologically r

Tutorials

ControlAudio: Tackling Text-Guided, Timing-Indicated and Intelligible Audio Generation via Progressive Diffusion Modeling

arXiv:2510.08878v3 Announce Type: replace-cross Abstract: Text-to-audio (TTA) generation with fine-grained control signals, e.g., precise timing control or intelligible speech content, has been explor

tutorialsarxiv-cs-cl

Hardware

Copy-as-Decode: Grammar-Constrained Parallel Prefill for LLM Editing

arXiv:2604.18170v1 Announce Type: new Abstract: LLMs edit text and code by autoregressively regenerating the full output, even when most tokens appear verbatim in the input. We study Copy-as-Decode, a

hardwarearxiv-cs-cl

CreditDecoding: Accelerating Parallel Decoding in Diffusion Large Language Models with Trace Credit

arXiv:2510.06133v2 Announce Type: replace Abstract: Diffusion large language models (dLLMs) generate text through iterative denoising. In commonly adopted parallel decoding schemes, each step confirms

Cross-Modal Bayesian Low-Rank Adaptation for Uncertainty-Aware Multimodal Learning

arXiv:2604.16657v1 Announce Type: new Abstract: Large pre-trained language models are increasingly adapted to downstream tasks using parameter-efficient fine-tuning (PEFT), but existing PEFT methods a

Tutorials

Cross-Modal Generation: From Commodity WiFi to High-Fidelity mmWave and RFID Sensing

arXiv:2604.16558v1 Announce Type: new Abstract: AIGC has shown remarkable success in CV and NLP, and has recently demonstrated promising potential in the wireless domain. However, significant data imb

tutorialsarxiv-cs-lg

Data Compressibility Quantifies LLM Memorization

arXiv:2507.06056v4 Announce Type: replace Abstract: Large Language Models (LLMs) are known to memorize portions of their training data, sometimes even reproduce content verbatim when prompted appropri

Decisive: Guiding User Decisions with Optimal Preference Elicitation from Unstructured Documents

arXiv:2604.18122v1 Announce Type: new Abstract: Decision-making is a cognitively intensive task that requires synthesizing relevant information from multiple unstructured sources, weighing competing f

DeepRitzSplit Neural Operator for Phase-Field Models via Energy Splitting

arXiv:2604.18261v1 Announce Type: cross Abstract: The multi-scale and non-linear nature of phase-field models of solidification requires fine spatial and temporal discretization, leading to long compu

Demystifying the unreasonable effectiveness of online alignment methods

arXiv:2604.17207v1 Announce Type: cross Abstract: Iterative alignment methods based on purely greedy updates are remarkably effective in practice, yet existing theoretical guarantees of (O(log T)) KL-

safetyarxiv-cs-cl

Disentangled Robot Learning via Separate Forward and Inverse Dynamics Pretraining

arXiv:2604.16391v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have shown great potential in building generalist robots, but still face a dilemma-misalignment of 2D image foreca

Do LLM-derived graph priors improve multi-agent coordination?

arXiv:2604.17191v1 Announce Type: new Abstract: Multi-agent reinforcement learning (MARL) is crucial for AI systems that operate collaboratively in distributed and adversarial settings, particularly i

Do LLMs Encode Functional Importance of Reasoning Tokens?

arXiv:2601.03066v2 Announce Type: replace Abstract: Large language models solve complex tasks by generating long reasoning chains, achieving higher accuracy at the cost of increased computational cost

DOSE: Data Selection for Multi-Modal LLMs via Off-the-Shelf Models

arXiv:2604.16979v1 Announce Type: cross Abstract: High-quality and diverse multimodal data are essential for improving vision-language models (VLMs), yet existing datasets often contain noisy, redunda

safetyarxiv-cs-cl

DuQuant++: Fine-grained Rotation Enhances Microscaling FP4 Quantization

arXiv:2604.17789v1 Announce Type: cross Abstract: The MXFP4 microscaling format, which partitions tensors into blocks of 32 elements sharing an E8M0 scaling factor, has emerged as a promising substrat

EdgeVTP: Exploration of Latency-efficient Trajectory Prediction for Edge-based Embedded Vision Applications

arXiv:2604.16783v1 Announce Type: new Abstract: Vehicle trajectory prediction is central to highway perception, but deployment on roadside edge devices necessitates bounded, deterministic end-to-end l

Efficient Diffusion Models under Nonconvex Equality and Inequality constraints via Landing

arXiv:2604.17838v1 Announce Type: new Abstract: Generative modeling within constrained sets is essential for scientific and engineering applications involving physical, geometric, or safety requiremen

safetyarxiv-cs-lg