Search: “context”

Enabling Knowledge Graph Understanding at Scale with the EXplore Your Graphs ENgine (EXYGEN)

arXiv:2609.11569v1 Announce Type: cross Abstract: We present EXYGEN (EXplore Your Graphs ENgine), a framework for knowledge graph (KG) understanding that enables conversational access to KGs at scale.

11 Sept 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

MC-DeTra: Motion-Consistent Joint Object Detection and Socially-Aware Trajectory Forecasting in Bird's-Eye-View Images

DGX agent

arXiv:2609.11717v1 Announce Type: new Abstract: Unified models for object detection and trajectory forecasting aim to merge perception and prediction for autonomous driving, refining actor trajectorie

model-releasesarxiv-cs-cv

11 Sept 2026

On the Relation between Code Quality and Machine Learning Performance: A Large-scale Empirical Study

arXiv:2609.10610v1 Announce Type: cross Abstract: Context: Computational notebooks are the standard environment for machine learning (ML) development. Within the ML community, model performance is oft

researcharxiv-cs-lg

11 Sept 2026

Co-Evolving Harnesses and Models: On-Policy Correction Helps Weaker Models Catch Up Where Imitation Fails

arXiv:2609.09134v1 Announce Type: new Abstract: Agent harnesses (the system prompt, tool set, execution hooks, and context-management scaffolding around a model) are a critical determinant of agentic

Control Copy-Paste: Controllable Diffusion-Based Augmentation Method for Remote Sensing Few-Shot Object Detection

arXiv:2507.21816v1 Announce Type: cross Abstract: Few-shot object detection (FSOD) for optical remote sensing images aims to detect rare objects with only a few annotated bounding boxes. The limited t

safetyarxiv-cs-cv

Tutorials

Cross-Species Animal Re-Identification with Semantic Consistency Learning

arXiv:2609.09705v1 Announce Type: new Abstract: Generalizable animal Re-Identification (ReID) aims to recognize individual animals across species with diverse morphologies and ecological contexts. Unl

tutorialsarxiv-cs-cv

Dimensionality Reduction for Hyperspectral Image Classification

arXiv:2609.10334v1 Announce Type: new Abstract: This paper addresses the issue of supervised classification in the context of hyperspectral satellite images. It deals with two fundamental aspects: dim

researcharxiv-cs-cv

Local Ai

Distilling Vision-Language Models for On-Device Fire Understanding

arXiv:2609.05782v1 Announce Type: new Abstract: Vision-language models (VLMs) offer a promising alternative to conventional fire detection systems by reasoning about the semantic context of a scene an

local-aiarxiv-cs-ai

Do Web Agents Investigate Before They Decide?

arXiv:2602.05354v3 Announce Type: replace Abstract: Autonomous web agents are increasingly deployed in moderation and policy enforcement, where correct decisions often depend on evidence that is not i

In RAG We Trust? Measuring Robustness of Retrieval-Augmented Generation Under Document Poisoning

arXiv:2609.09243v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) grounds a language model in retrieved documents, which reduces hallucination but creates a new attack surface: if

ProMeta: Few-shot PROTAC-targeted degradation prediction across E3 ligases

arXiv:2609.09891v1 Announce Type: new Abstract: Proteolysis-targeting chimeras (PROTACs) have emerged as a transformative therapeutic strategy that selectively degrades historically ''undruggable'' ta

Reproducing Omitted Temporal Expressions in Japanese News for Retrieval-Augmented Applications

arXiv:2609.09569v1 Announce Type: new Abstract: News articles often contain omitted temporal expressions, such as day-only or month-only mentions, which must be interpreted with reference to the publi

researcharxiv-cs-cl

Revisiting the Shape Convention of Transformer Language Models

arXiv:2602.06471v2 Announce Type: replace Abstract: The architectural shape of dense Transformers has remained remarkably stable: narrow-wide-narrow feed-forward networks (FFNs) consume most non-embed

Local Ai

ScopeMamba-YOLO: Widening the Perceptual Scope Inward and Outward for Small Object Detection in Remote Sensing Imagery

arXiv:2609.10156v1 Announce Type: new Abstract: Small object detection in unmanned aerial vehicle (UAV) and remote sensing imagery requires preserving high-resolution detail while modeling long-range

local-aiarxiv-cs-cv

A*-Thought-V2: Efficient Latent Reasoning via Geometric Dynamics of LLM

arXiv:2609.07821v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) improves the reasoning ability of Large Language Models (LLMs) but incurs substantial computation and context costs. Existing m

safetyarxiv-cs-lg

Dual-Latent Memory Routing for Vision-Language Reasoning

model-releasesarxiv-cs-cv

arXiv:2609.05539v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have recently made strong progress in vision-language reasoning, yet their performance often degrades as genera

How Long Until Your Robot Ignores You? A Safety Benchmark for LLM Orchestrators in Human-Humanoid Collaboration

model-releasesarxiv-cs-ro

arXiv:2609.07288v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly employed to orchestrate robot behavior through natural-language interfaces, yet no benchmark exists to eva

Imaginative World Modeling with Scene Graphs for Embodied Agent Navigation

arXiv:2508.06990v2 Announce Type: replace Abstract: Semantic navigation requires an agent to navigate toward a specified target in an unseen environment. Employing an imaginative navigation strategy t

agentsarxiv-cs-ro

Hardware

Kalman Delta Networks: Uncertainty-aware Associative Memory

arXiv:2609.07816v1 Announce Type: new Abstract: Linear attention is increasingly used in frontier language models for efficient long-context inference and constant-memory decoding. Its fixed-size recu

hardwarearxiv-cs-lg

Learning Length-Extrapolatable Recurrent Models

arXiv:2609.09157v1 Announce Type: new Abstract: Recurrent models provide a natural path to long-context modeling, yet models trained with backpropagation through time (BPTT) often fail beyond their tr

MARS-CLIP: Multi-Resolution and Attention Refined Zero-Shot Image Segmentation

arXiv:2609.08283v1 Announce Type: new Abstract: Contrastive Language-Image Pre-training (CLIP) has demonstrated impressive capabilities in zero-shot transfer but often struggles with dense prediction

researcharxiv-cs-cv

Local Ai

Model-Adaptive and Risk-Constrained Frequency Hopping Against Predictive Jammers

arXiv:2609.06514v1 Announce Type: new Abstract: Adaptive frequency hopping against predictive jamming must address both model uncertainty and policy exposure: the context-loss relationship may vary ac

local-aiarxiv-cs-lg

Patient-Specific Articulated Digital Twins from a Single Full-Body CT Scan

arXiv:2607.02156v2 Announce Type: replace Abstract: Patient-specific anatomical models provide individualized context for surgical planning, image-guided intervention, and algorithm development. Howev

researcharxiv-cs-cv

RoboDreamer: Anticipatory Humanoid Locomotion with Predictive State-Space Models

arXiv:2609.07096v1 Announce Type: new Abstract: Humanoid locomotion requires control policies that remain stable under imperfect sensing while exploiting temporal context for consistent motion. We pre

safetyarxiv-cs-ro

Spheriverse: 3D Scene Understanding from Spherical Observations in the Wild

model-releasesarxiv-cs-cv

arXiv:2609.09012v1 Announce Type: new Abstract: Spherical observations provide global visual context for 3D scene understanding. However, visual information is encoded in an angular domain, whereas th

Steering Geometry: Validating Human Value Geometry in LLM Steering Space

arXiv:2609.06289v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed in alignment-sensitive contexts, activation steering has emerged as a lightweight, inference

Towards Unified Multimodal Graph Foundation Model: A Bridge-Router-Adapter Based Approach

arXiv:2609.06668v1 Announce Type: new Abstract: Multimodal graphs couple node attributes in different modalities, such as text and images, with relational structure, enabling topological structure and

researcharxiv-cs-lg

Tutorials

Adapting from Downturns: Prediction of Long-Term Conversational-Skill Development in Mental-Health Crisis Counselors

arXiv:2609.04350v1 Announce Type: cross Abstract: How do people learn to become better conversationalists? This question is especially important in the context of mental-health counseling, where conve

tutorialsarxiv-cs-ai

Constructing and Evaluating Clinical Reasoning Trajectories for Medical Agent

arXiv:2609.05090v1 Announce Type: new Abstract: Evaluation of medical artificial intelligence agents remains predominantly answer-centric, assessing only the correctness of final outputs while overloo

agentsarxiv-cs-ai

Controlling and Assessing Appropriate Persona Use in LLM-based Dialogue Generation

arXiv:2609.04676v1 Announce Type: new Abstract: In persona-based dialogue generation (PDG), LLMs often overuse persona attributes by incorporating them regardless of dialogue context, resulting in unn

safetyarxiv-cs-cl

Diffusion Language Models for Mobile Edge Agentic AI: Foundations, Applications, and Challenges

arXiv:2609.04778v1 Announce Type: new Abstract: Diffusion language models (DLMs) offer a non-autoregressive alternative for mobile edge agentic artificial intelligence (AI) by refining tokens through

agentsarxiv-cs-ai

Discourse Dependency: A Continuous Criterion for Translation Difficulty

arXiv:2609.04959v1 Announce Type: new Abstract: Recent calls for harder machine translation benchmarks have not clarified what difficulty should mean. We argue that one meaningful and currently unmeas

researcharxiv-cs-cl

MCPO: Modality-Contrastive Preference Optimization for Multimodal Chain-of-Thought Compression

arXiv:2609.04947v1 Announce Type: cross Abstract: Recently, multimodal large-scale reasoning models have demonstrated remarkable capabilities in solving complex tasks through long Chains-of-Thought (M

safetyarxiv-cs-ai

Patterns of Priming in Production: Lexical, Semantic and Structural Alignment in Language Model Generation

arXiv:2609.04484v1 Announce Type: cross Abstract: This paper investigates structural priming in language model (LM) production, examining how preceding structural context influences sentence completio

safetyarxiv-cs-ai

Uncertainty Signals for Network Intent Translation: Risk Ranking and Ambiguity Localization

arXiv:2609.04486v1 Announce Type: cross Abstract: Intent-based networking realization starts by translating high-level intents into low-level network configurations. Recent approaches have shifted tow

What Attention Recalls and Recurrence Controls in Hybrid Language Models

arXiv:2609.04434v1 Announce Type: new Abstract: Hybrid language models combine attention with a fixed-size recurrent state, but the role of each channel remains unclear. We introduce two cache-level i

researcharxiv-cs-cl

B2B Customer Conversion Prediction: A Document Representation, Graph Theory, and CatBoost Driven Methodology

arXiv:2609.03239v1 Announce Type: new Abstract: In the one-time selling B2B context, the buying cycle may last months or even years. During the long process, targeting customers that have a high poten

researcharxiv-cs-lg

CASCADE: A Component Ablation and Corpus Audit of a Layered Local Defense for MCP-Based Systems

arXiv:2604.17125v2 Announce Type: replace-cross Abstract: The Model Context Protocol (MCP) widens the prompt injection attack surface of large language model applications to tool descriptions, paramet

Caught in the Story: Narrative Captivity in Multi-turn LLMs Conversation

arXiv:2609.03407v1 Announce Type: new Abstract: People increasingly turn to large language models (LLMs) for everyday advice, making ethically charged interpersonal problems a practical moral-advisory

Dude: A Dual-Detection Multi-Agent System for Paper-Code Discrepancy Detection

arXiv:2609.03416v1 Announce Type: new Abstract: LLM-empowered paper-code discrepancy detection has received growing concern since the scaling of research submissions exceeds the manual review capabili

agentsarxiv-cs-ai

Margins, Not Windows: Training-Free Per-Step Lossy Speculative Decoding

arXiv:2609.02897v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference by drafting candidate tokens and verifying them in parallel. Tree-attention drafters such as EAGLE-3 are

No country for old linguists: LLM-brain alignment underdetermines neural computation

arXiv:2609.03160v1 Announce Type: new Abstract: Nastase et al. (2026) argue that large language models (LLMs) may illuminate language processing because both rely on distributed, context-sensitive rep

safetyarxiv-cs-cl

Pattern Over-Generalization of Knowledge Graph Embedding

arXiv:2609.03487v1 Announce Type: cross Abstract: Knowledge graph embedding (KGE) demonstrates its effectiveness for predicting missing links in knowledge graphs (KGs) by projecting entities and relat

SignSeek: Learning Transferable Representations for Sign Dictionary Retrieval

arXiv:2609.03695v1 Announce Type: new Abstract: Sign language dictionaries are essential resources for sign language learners, yet automatically retrieving a sign from a dictionary, given only a query

safetyarxiv-cs-cv

WorldReward: Reward Modeling for Camera-Conditioned World Models

model-releasesarxiv-cs-cv

arXiv:2609.03952v1 Announce Type: new Abstract: Camera-conditioned world models generate interactive videos in which commanded actions should induce the expected scene changes while appearance, geomet

Bridging Latent Reasoning and Target-Language Generation via Retrieval-Transition Heads

arXiv:2602.22453v3 Announce Type: replace Abstract: Recent work has identified a subset of attention heads in Transformer as retrieval heads, which are responsible for retrieving information from the

3 Sept 2026

CHASE: Cache-Hole-Adapted Skip Exit for Looped State-Space Language Models

arXiv:2607.10110v2 Announce Type: replace Abstract: Recent work on looped language models suggests that many reasoning problems benefit from greater computational depth rather than from additional ind

3 Sept 2026

DocHop: Benchmarking Out-of-domain Multi-hop Reasoning in Information-Dense Documents

arXiv:2609.02059v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved strong performance on structured visual understanding tasks such as chart and document question a