Search: “inference”

JACoP: Joint Alignment for Compliant Multi-Agent Prediction

arXiv:2605.11385v1 Announce Type: new Abstract: Stochastic Human Trajectory Prediction (HTP) using generative modeling has emerged as a significant area of research. Although state-of-the-art models e

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Latent Causal Void: Explicit Missing-Context Reconstruction for Misinformation Detection

DGX agent

arXiv:2605.12156v1 Announce Type: new Abstract: Automatic misinformation detection performs well when deception is visible in what an article explicitly states. However, some misinformation articles r

model-releasesarxiv-cs-cl

13 May 2026

LEAP: Unlocking dLLM Parallelism via Lookahead Early-Convergence Token Detection

arXiv:2605.10980v1 Announce Type: new Abstract: Diffusion Language Models (dLLMs) have garnered significant attention for their potential in highly parallel processing. The parallel capabilities of ex

Leveraging RAG for Training-Free Alignment of LLMs

arXiv:2605.11217v1 Announce Type: new Abstract: Large language model (LLM) alignment algorithms typically consist of post-training over preference pairs. While such algorithms are widely used to enabl

Logit-Attention Divergence: Mitigating Position Bias in Multi-Image Retrieval via Attention-Guided Calibration

arXiv:2605.11591v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown strong performance in multi-image cross-modal retrieval, yet suffer from severe position bias, where

Agents

MAC: Masked Agent Collaboration Boosts Large Language Model Medical Decision-Making

arXiv:2507.21159v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have proven effective in artificial intelligence, where the multi-agent system (MAS) holds considerable promise f

agentsarxiv-cs-lg

Applications

Make It Long, Keep It Fast: End-to-End 10k-Sequence Modeling at Billion Scale on Douyin Recommendation

arXiv:2511.06077v2 Announce Type: replace Abstract: Short-video recommenders such as Douyin must exploit extremely long user histories without breaking latency or cost budgets. We present an end-to-en

applicationsarxiv-cs-lg

MedHopQA: A Disease-Centered Multi-Hop Reasoning Benchmark and Evaluation Framework for LLM-Based Biomedical Question Answering

arXiv:2605.12361v1 Announce Type: new Abstract: Evaluating large language models (LLMs) in the biomedical domain requires benchmarks that can distinguish reasoning from pattern matching and remain dis

Mitigating Action-Relation Hallucinations in LVLMs via Relation-aware Visual Enhancement

arXiv:2605.11808v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable performance on diverse vision-language tasks. However, LVLMs still suffer from hallucinati

local-aiarxiv-cs-cv

Monitoring access to piped water and sanitation infrastructure in Africa at disaggregated scales using satellite imagery and self-supervised learning

arXiv:2411.19093v4 Announce Type: replace Abstract: Access to drinking water and sanitation services is essential for health and well-being, yet large global disparities persist. Sustainable Developme

Tutorials

Multi-modal Bayesian Neural Network Surrogates with Conjugate Last-Layer Estimation

arXiv:2509.21711v2 Announce Type: replace-cross Abstract: As data collection and simulation capabilities advance, multi-modal learning, the task of learning from multiple modalities and sources of dat

tutorialsarxiv-cs-lg

@nvidia Nemotron native support in Deep Agents 0.6 #interrupt #langchain

model-releasesharrison-chase--x

NVIDIA Nemotron models received native support integration in Deep Agents version 0.6, enabling improved language model capabilities within the LangChain framework. This update allows developers to le

On the Approximation Complexity of Matrix Product Operator Born Machines

arXiv:2605.11471v1 Announce Type: new Abstract: Matrix product operator Born machines (MPO-BMs) are tractable tensor-network models for probabilistic modeling, but their efficient approximation capabi

Overcoming Dynamics-Blindness: Training-Free Pace-and-Path Correction for VLA Models

arXiv:2605.11459v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models achieve remarkable flexibility and generalization beyond classical control paradigms. However, most prevailing VLA

Parameter-Efficient Adaptation of Pre-Trained Vision Foundation Models for Active and Passive Seismic Data Denoising

arXiv:2605.10953v1 Announce Type: cross Abstract: The demand for high-resolution subsurface imaging and continuous Earth monitoring has driven rapid growth in active and passive seismic data from dens

Picasso: Holistic Scene Reconstruction with Physics-Constrained Sampling

arXiv:2602.08058v2 Announce Type: replace Abstract: In the presence of occlusions and measurement noise, geometrically accurate scene reconstructions -- which fit the sensor data -- can still be physi

PointCaM: Cut-and-Mix for Open-Set Point Cloud Learning

arXiv:2212.02011v3 Announce Type: replace Abstract: Point cloud learning is receiving increasing attention. However, most existing point cloud models lack the practical ability to deal with the unavoi

Predictive Maps of Multi-Agent Reasoning: A Successor-Representation Spectrum for LLM Communication Topologies

arXiv:2605.11453v1 Announce Type: cross Abstract: Practitioners deploying multi-agent large language model (LLM) systems must currently choose between communication topologies such as chain, star, mes

PRISM: A Geometric Risk Bound that Decomposes Drift into Scale, Shape, and Head

arXiv:2605.11608v1 Announce Type: new Abstract: Comparing post-training LLM variants, such as quantized, LoRA-adapted, and distilled models, requires a diagnostic that identifies how a variant has dri

PRISM: Pareto-Efficient Retrieval over Intent-Aware Structured Memory for Long-Horizon Agents

arXiv:2605.12260v1 Announce Type: new Abstract: Long-horizon language agents accumulate conversation history far faster than any fixed context window can hold, making memory management critical to bot

Prototype Fusion: A Training-Free Multi-Layer Approach to OOD Detection

arXiv:2603.23677v2 Announce Type: replace Abstract: Deep learning models are increasingly deployed in safety-critical applications, where reliable out-of-distribution (OOD) detection is essential to e

Applications

Quantifying the Reconstructability of Astrophysical Methods with Large Language Models and Information Theory: A Case Study in Spectral Reconstruction

arXiv:2605.11154v1 Announce Type: cross Abstract: Modern astrophysical studies rely heavily on complex data analysis pipelines; however, published descriptions often lack the detail required for compu

applicationsarxiv-cs-lg

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models

arXiv:2605.11887v1 Announce Type: new Abstract: Large language models have achieved remarkable capabilities across diverse tasks, yet their internal decision-making processes remain largely opaque, li

Ray-Aware Pointer Memory with Adaptive Updates for Streaming 3D Reconstruction

arXiv:2605.05749v2 Announce Type: replace Abstract: Dense 3D reconstruction from continuous image streams requires both accurate geometric aggregation and stable long-term memory management. Recent fe

local-aiarxiv-cs-cv

ReAD: Reinforcement-Guided Capability Distillation for Large Language Models

arXiv:2605.11290v1 Announce Type: new Abstract: Capability distillation applies knowledge distillation to selected model capabilities, aiming to compress a large language model (LLM) into a smaller on

researcharxiv-cs-cl

Real-Scale Island Area and Coastline Estimation using Only its Place Name or Coordinates

arXiv:2605.11267v1 Announce Type: new Abstract: Accurate measurement of island area and coastline length is crucial for coastal zone monitoring and oceanographic analysis. However, traditional measure

RealDiffusion: Physics-informed Attention for Multi-character Storybook Generation

arXiv:2605.11927v1 Announce Type: new Abstract: While modern diffusion models excel at generating diverse single images, extending this to sequential generation reveals a fundamental challenge: balanc

ReasonEdit: Editing Vision-Language Models using Human Reasoning

arXiv:2602.02408v4 Announce Type: replace Abstract: Model editing aims to correct errors in large, pretrained models without altering unrelated behaviors. While some recent works have edited vision-la

Applications

Reconstruction of Personally Identifiable Information from Supervised Finetuned Models

arXiv:2605.12264v1 Announce Type: cross Abstract: Supervised Finetuning (SFT) has become one of the primary methods for adapting a large language model (LLM) with extensive pre-trained knowledge to do

applicationsarxiv-cs-cl

Revisiting Shadow Detection from a Vision-Language Perspective

arXiv:2605.11771v1 Announce Type: new Abstract: Shadow detection is commonly formulated as a vision-driven dense prediction problem, where models rely primarily on pixel-wise visual supervision to dis

RT-Transformer: The Transformer Block as a Spherical State Estimator

arXiv:2605.11007v1 Announce Type: new Abstract: We show that the core components of the Transformer block -- attention, residual connections, and normalization -- arise naturally from a single geometr

@SakanaAILabs @NVIDIAAI Sparser, Faster, Lighter Transformer Language Models https://arxiv.org/abs/2603.23198

This research paper from Sakana AI and NVIDIA explores techniques for creating more efficient transformer language models by reducing sparsity, computational requirements, and model size while maintai

researchdavid-ha--x

Sampling More, Getting Less: Calibration is the Diversity Bottleneck in LLMs

arXiv:2605.11128v1 Announce Type: new Abstract: Diversity is essential for language-model applications ranging from creative generation to scientific discovery, yet modern LLMs often collapse into a n

See the past: Time-Reversed Scene Reconstruction from Thermal Traces Using Visual Language Models

arXiv:2510.05408v2 Announce Type: replace Abstract: Recovering the past from present observations is an intriguing challenge with potential applications in forensics and scene analysis. Thermal imagin

Semi-Supervised Bayesian GANs with Log-Signatures for Uncertainty-Aware Credit Card Fraud Detection

arXiv:2509.00931v3 Announce Type: replace-cross Abstract: We present a novel deep generative semi-supervised framework for credit card fraud detection, formulated as time series classification task. A

Agents

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

arXiv:2605.12500v1 Announce Type: new Abstract: Recent large vision-language models (VLMs) remain fundamentally constrained by a persistent dichotomy: understanding and generation are treated as disti

agentsarxiv-cs-cv

Tutorials

Sharpen Your Flow: Sharpness-Aware Sampling for Flow Matching

arXiv:2605.11547v1 Announce Type: new Abstract: Flow matching models generate samples by numerically integrating a learned velocity field, with each integration step requiring a neural network evaluat

tutorialsarxiv-cs-lg

Solve the Loop: Attractor Models for Language and Reasoning

arXiv:2605.12466v1 Announce Type: cross Abstract: Looped Transformers offer a promising alternative to purely feed-forward computation by iteratively refining latent representations, improving languag

SOMA: Efficient Multi-turn LLM Serving via Small Language Model

arXiv:2605.11317v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in multi-turn dialogue settings where preserving conversational context across turns is essential

Sparse Attention Remapping with Clustering for Efficient LLM Decoding on PIM

arXiv:2505.05772v2 Announce Type: replace Abstract: Transformer-based models are the foundation of modern machine learning, but their execution, particularly during autoregressive decoding in large la

researcharxiv-cs-cl

SRG: Score-based Relaxation-guided Generation for Mixed Integer Linear Programming

arXiv:2603.24033v2 Announce Type: replace Abstract: We propose Score-based Relaxation-guided Generation (SRG), a generative framework based on an approximate formulation of relaxation-guided stochasti

TB-AVA: Text as a Semantic Bridge for Audio-Visual Parameter Efficient Finetuning

arXiv:2605.11572v1 Announce Type: new Abstract: Audio-visual understanding requires effective alignment between heterogeneous modalities, yet cross-modal correspondence remains challenging when tempor

TextSeal: A Localized LLM Watermark for Provenance & Distillation Protection

arXiv:2605.12456v1 Announce Type: cross Abstract: We introduce TextSeal, a state-of-the-art watermark for large language models. Building on Gumbel-max sampling, TextSeal introduces dual-key generatio

The DAWN of World-Action Interactive Models

arXiv:2605.11550v1 Announce Type: new Abstract: A plausible scene evolution depends on the maneuver being considered, while a good maneuver depends on how the scene may evolve. Existing World Action M

Think, then Score: Decoupled Reasoning and Scoring for Video Reward Modeling

arXiv:2605.05922v2 Announce Type: replace Abstract: Recent advances in generative video models are increasingly driven by post-training and test-time scaling, both of which critically depend on the qu

Today we release Token Superposition Training (TST), a modification to the standard LLM pretraining loop that produces a 2-3× wall-clock spe…

Today we release Token Superposition Training (TST), a modification to the standard LLM pretraining loop that produces a 2-3× wall-clock speedup at matched FLOPs without changing the model architectur

researchnous-research--x

Towards Order Fairness: Mitigating LLMs Order Sensitivity through Dual Group Advantage Optimization

arXiv:2605.11974v1 Announce Type: new Abstract: Large Language Models (LLMs) suffer from order bias, where their performance is affected by the arrangement order of input elements. This unfairness lim

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data

arXiv:2605.11170v1 Announce Type: new Abstract: Noise-based certified machine unlearning currently faces a hard ceiling: the noise magnitude required to certify unlearning typically destroys model uti