Search: “inference”

Do Language Models Consistently Encode the Current Year?

arXiv:2608.15507v1 Announce Type: new Abstract: A consistent concept of the current time is important for temporal reasoning, yet how language models represent the current time is not well understood.

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Do Uncertainty Signals Help? A Systematic Study of Uncertainty-Aware Decoding with Rollback Mechanisms

DGX agent

arXiv:2608.14653v1 Announce Type: cross Abstract: Prediction uncertainty is a widely adopted metric for quantifying model confidence, with downstream applications spanning model explanation, data sele

researcharxiv-cs-ai

18 Aug 2026

Domain-Agnostic Neural Topic Modeling with Contextual Token-Level Semantic Graph Representation

model-releasesarxiv-cs-cl

arXiv:2608.16269v1 Announce Type: new Abstract: Recent advances in neural topic models with pre-trained language models (PLMs) have achieved strong performance by leveraging general-domain pre-trainin

DRAFE: Domain-Robust Asymmetric Fusion of Heterogeneous Detection Transformers for Cross-City Fine-Grained Traffic Object Detection

model-releasesarxiv-cs-cv

arXiv:2608.16632v1 Announce Type: new Abstract: Deep learning-based object detectors are fundamental to intelligent transportation systems, enabling traffic monitoring, vehicle analytics, and infrastr

DR.GAP: Mitigating Bias in Large Language Models using Gender-Aware Prompting with Decoupled Reasoning

arXiv:2502.11603v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) exhibit strong natural language understanding capabilities but also inherit and amplify societal biases, particul

safetyarxiv-cs-ai

DSPrompt: Dynamic Soft Prompt Defense Against M-RAG Corruption

arXiv:2608.16536v1 Announce Type: cross Abstract: Multimodal Retrieval Augmented Generation (M-RAG) is increasingly vulnerable to adversarial attacks where malicious data are crafted to produce embedd

researcharxiv-cs-cl

DumpsterCluster: From Dumpster Diving to Serving LLaMA-70B on $60 GPUs

arXiv:2608.14614v1 Announce Type: cross Abstract: As AI datacenters retire functional GPUs, vast quantities of still capable accelerators enter secondary markets. This paper investigates whether these

EA-LiteUNet: An Edge-Adaptive and Resource-Efficient U-Net for Boundary-Sensitive Dermoscopic Image Segmentation

arXiv:2608.15537v1 Announce Type: cross Abstract: Accurate boundary delineation remains a persistent challenge in dermoscopic image segmentation because of blurred lesion margins, heterogeneous textur

Applications

EgoTac: In-the-wild Tactile Prediction from Egocentric Vision

arXiv:2608.15060v1 Announce Type: new Abstract: Touch is fundamental to dexterous manipulation, yet most egocentric human data increasingly used for robot learning lacks tactile information. Directly

applicationsarxiv-cs-cv

Eigenanalysis framework for autoregressive neural emulators of multi-scale chaotic dynamics

arXiv:2608.16084v1 Announce Type: new Abstract: Neural autoregressive models have rapidly emerged as powerful emulators of high-dimensional chaotic systems, yet their long-term instability and error g

safetyarxiv-cs-ai

Euclid-Omni : A Unified Neuro-Symbolic Framework for Plane Geometry

arXiv:2608.14585v1 Announce Type: new Abstract: Euclidean geometry is a compelling testbed for AI reasoning, as it demands the combination of intuitive diagram understanding, axiomatic deduction, and

Tutorials

Evidence of Absence: Cross-Modal Abductive Risk Perception to Sustain World Models When Vision Fails

arXiv:2608.14952v1 Announce Type: cross Abstract: A structured world-state (entities, relations, context, and predictive cues) is designed to preserve prediction-critical content when perception degra

tutorialsarxiv-cs-cv

Executable Code Knowledge: Code as a Native, Validation-Carrying Knowledge Representation for AI Coding Agents

arXiv:2608.16295v1 Announce Type: new Abstract: AI coding agents need more than relevant snippets: they need business semantics, validation evidence, relations, and assurance that their context is cur

local-aiarxiv-cs-cl

FLEET: Token-Based Feature Extraction for Event Camera-based Reinforcement Learning

model-releasesarxiv-cs-cv

arXiv:2608.16523v1 Announce Type: new Abstract: Event cameras generate asynchronous, high-frequency data streams offering spatially sparse information at lower latency than traditional cameras.In prin

FloodReasonBench: Benchmarking VLM Reasoning Segmentation for Embodied Flood Response at the Edge

arXiv:2608.15410v1 Announce Type: cross Abstract: Reasoning segmentation enables vision-language models (VLMs) to translate mission-relevant language requests into pixel-level visual grounding, offeri

From Generalist to Specialist: A Context-Fusion Framework for Endoscopic Polyp Reporting with a Frozen VLM

arXiv:2608.15580v1 Announce Type: new Abstract: Reliable endoscopic polyp reporting requires integrating quantitative lesion sizing, standardized Paris classification, and clinically meaningful morpho

Agents

From Prompts to Constructs: A Dual-Validity Framework for Large Language Model Research in Psychology

arXiv:2506.16697v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are entering psychological research both as tools and as objects of inquiry. Yet many studies apply human instrum

agentsarxiv-cs-ai

From 'What-If' to 'What-Is': Counterfactual Thinking-Inspired Semantic Alignment for Visual Brain Decoding

arXiv:2608.15163v1 Announce Type: new Abstract: Visual brain decoding reconstructs visual content perceived by a person from neural measurements such as fMRI, providing a computational approach to stu

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Frontier AI Forecasting Has a Measurement Problem: An Audit of Progress Evidence

arXiv:2608.14903v1 Announce Type: new Abstract: Quantitative forecasts of frontier artificial intelligence often connect dated targets to trends in benchmark scores, training compute, release time, or

GenRouter: Unified Workflow Routing for Agentic Image Generation

arXiv:2608.16721v1 Announce Type: new Abstract: The rapid evolution of text-to-image (T2I) generation models has effectively solved the foundational challenge of raw pixel synthesis, shifting the comm

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GLaQ: Grounding Latent Queries in Visual Evidence for Multimodal Reasoning

arXiv:2608.15517v1 Announce Type: new Abstract: Chain-of-thought reasoning has substantially improved the problem-solving capabilities of multimodal large language models. Fine-grained visual evidence

local-aiarxiv-cs-cv

Applications

GOD: Enhancing Generalization via Deep Grafting for Sequential Recommendation

arXiv:2608.16073v1 Announce Type: cross Abstract: Sequential recommenders often struggle with sparse and noisy histories, limiting generalization to unseen interactions. Knowledge distillation mitigat

applicationsarxiv-cs-lg

Hierarchical Adaptive Feature Refinement Network for VHR Remote Sensing Image Segmentation

arXiv:2608.15647v1 Announce Type: cross Abstract: Semantic segmentation of very-high-resolution (VHR) remote sensing imagery increasingly benefits from strong pretrained hierarchical encoders, yet exp

local-aiarxiv-cs-ai

HiFi-BRep: High-Fidelity Latent Representation for Robust B-Rep Generation

arXiv:2608.16485v1 Announce Type: new Abstract: Boundary representation (B-Rep) generation is a fundamental task in computer-aided design, yet the direct synthesis of high-fidelity and structurally va

researcharxiv-cs-cv

Tutorials

HOIMask: Towards Generative Masked Modeling for Human Object Interaction Generation

arXiv:2608.15141v1 Announce Type: new Abstract: Diffusion-based methods have dominated the HOI generation, as they enable critical contact fusions or signals to guide the diffusion process. However, t

tutorialsarxiv-cs-cv

I-CALM: Incentivizing Confidence-Aware Abstention for LLM Selective Answering

arXiv:2604.03904v2 Announce Type: replace-cross Abstract: Large language models (LLMs) often produce confident but incorrect answers, in part because standard evaluation incentives reward guessing ove

iFuzz-Meta: An Interpretable Fuzzy Learning Framework Bridging Top-Down and Bottom-Up Knowledge Integration

arXiv:2608.14646v1 Announce Type: cross Abstract: Interpretable representation learning remains a key challenge in modern neural computation, particularly when models are expected not only to perform

Intent-Driven Situation Tracking for User-Centric Multi-Turn Agents

arXiv:2608.15755v1 Announce Type: new Abstract: User-centric multi-turn agents must act on an evolving task situation shaped by changing user intents, accumulated tool-grounded facts, missing informat

Interactive Whole Slide Images for RL-based Tumour Segmentation

arXiv:2608.16607v1 Announce Type: new Abstract: Whole-slide image (WSI) analysis remains computationally challenging due to the extremely large spatial resolution of slides and the sparse distribution

local-aiarxiv-cs-cv

Interpretable Cross-Lingual Alignment in Small Language Models: Probing Cultural and Pragmatic Reasoning in Japanese-English Bilingual LLMs

model-releasesarxiv-cs-cl

arXiv:2608.14896v1 Announce Type: new Abstract: Large language models work well on English and behave in poorly understood ways on languages typologically far from it. Japanese is a clean example, whe

Invariant Pretraining for Robust Code Representations

arXiv:2608.15412v1 Announce Type: cross Abstract: Encoder-based code representation models remain widely deployed for discriminative tasks such as clone detection and code classification, where their

KOALA: Koopman Operator Learning for WiFi-Based Anticipatory Hum

arXiv:2608.15815v1 Announce Type: new Abstract: WiFi Channel State Information (CSI) has emerged as a privacy-preserving alternative to cameras for human pose estimation. However, existing approaches

researcharxiv-cs-lg

KV-Rescue: Recovering Reasoning Language Model KV Eviction Loss via Stepwise Interleaving

arXiv:2608.15797v1 Announce Type: new Abstract: KV-cache eviction caps the memory cost of long reasoning traces but is inherently lossy because the model decodes from a partial view of its history. Un

Large Language Models Show Metacognitive Sensitivity in Medical Reasoning

arXiv:2608.14552v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly evaluated and used in medicine, but clinical usefulness depends on answer accuracy and whether confidence

LlamaRec-LKG-RAG: A Single-Pass, Learnable Knowledge Graph-RAG Framework for LLM-Based Ranking

arXiv:2506.07449v2 Announce Type: replace-cross Abstract: Recent advances in Large Language Models (LLMs) have driven their adoption in recommender systems through Retrieval-Augmented Generation (RAG)

LLMs as a Jury: Cross-Model Consensus Can Outperform Process Reward Models for LLM Reasoning

arXiv:2607.10139v3 Announce Type: replace-cross Abstract: Selecting the correct answer from a pool of candidate reasoning chains is the engine of test-time scaling, yet the standard selectors each car

Agents

MELD: A Protocol for Merging Knowledge Across Distributed Agentic Memories

arXiv:2608.16357v1 Announce Type: cross Abstract: Autonomous agents share a transport and can call each other's tools, but they cannot share what they know: no protocol lets two agents' memories recon

agentsarxiv-cs-ai

Mitigating Rubric Interference in LLM Judges via On-Policy Self-Distillation

arXiv:2608.14684v1 Announce Type: cross Abstract: LLM judges increasingly evaluate responses against fine-grained rubric checklists. When a sample requires multiple rubrics, current methods typically

MLLM-Guided Semantic Correction for Text-to-Video Generation

arXiv:2608.16513v1 Announce Type: cross Abstract: Recent advances in diffusion models and Transformer architectures have led to significant progress in text-to-video generation. However, these models

safetyarxiv-cs-ai

Model Inversion Attacks: A Survey of Approaches and Countermeasures

arXiv:2411.10023v3 Announce Type: replace Abstract: Deep neural networks have enabled numerous studies and applications on both Euclidean data, such as images and text, and non-Euclidean data, such as

researcharxiv-cs-lg

MOSS-VL Technical Report

arXiv:2608.15045v1 Announce Type: new Abstract: We present MOSS-VL, an open vision-language model family that treats real-time interaction -- perceiving while it speaks -- as a first-class capability.

researcharxiv-cs-cv

Nexus: Structured Synergy for Efficient Text-to-Image Generation using Rectified Flow Model

arXiv:2608.16104v1 Announce Type: new Abstract: Diffusion and flow matching models have made significant progress in text-to-image generation, yet high computation, quadratic complexity, and large mem

researcharxiv-cs-cv

OvDSGG: End-to-End Open-Vocabulary Dynamic Scene Graph Generation

model-releasesarxiv-cs-cv

arXiv:2608.14835v1 Announce Type: new Abstract: Dynamic scene graphs (DSGs) capture spatio-temporal interactions across videos as langlesubject, predicate, objectrangle triplets, and underpin downstre

P2E-VQ: ECG-linked representation augmentation for PPG via discrete patch retrieval

arXiv:2608.14656v1 Announce Type: cross Abstract: Photoplethysmography (PPG) is widely used in consumer wearables because of its low cost and ease of acquisition. However, unlike electrocardiography (

PerFACT: Motion Policy with LLM-Powered Dataset Synthesis and Fusion Action-Chunking Transformers

model-releasesarxiv-cs-ro

arXiv:2512.03444v2 Announce Type: replace Abstract: Deep learning methods have significantly enhanced motion planning for robotic manipulators by leveraging prior experiences within planning datasets.

PertMind: Eliciting Emergent Biological Reasoning in LLM via Reinforcement Learning on Cellular Perturbation Data

arXiv:2608.16419v1 Announce Type: cross Abstract: Large language models can describe mechanisms, yet scalable post-training still depends on costly, manually curated biological reasoning traces. Here

Phase-Aware CNN for Real-Time 5G/6G Channel Estimation with Hardware-in-the-loop Validation

arXiv:2608.14676v1 Announce Type: cross Abstract: In 5G/6G wireless systems, accurate and timely channel estimation is critical to ensure reliable communication under complex, fast-changing radio cond

researcharxiv-cs-lg

Physiological World Models for Human State Transitions

arXiv:2608.15309v1 Announce Type: new Abstract: Continuous multimodal sensing now allows human physiology to be observed throughout daily life rather than only during occasional clinical visits. Howev