Search: “retrieval”

UltRAG: a Universal Simple Scalable Recipe for Knowledge Graph RAG

model-releasesarxiv-cs-cl

arXiv:2603.28773v2 Announce Type: replace-cross Abstract: Large language models (LLMs) frequently generate confident yet factually incorrect content when used for language generation (a phenomenon oft

30 Sept 2026

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Model Releases

VideoLoop: Looped Working Memory Against Semantic Thrashing in Long-Form Video Agents

DGX agent

arXiv:2609.38119v1 Announce Type: new Abstract: Long-form video understanding requires multimodal agents to iteratively gather evidence over many reasoning steps. However, most existing agentic method

model-releasesarxiv-cs-cv

30 Sept 2026

Agents

When Tools Silently Lie: Evaluating and Mitigating Blind Compliance in Tool-Augmented Data Agents

arXiv:2609.37153v1 Announce Type: new Abstract: Tool-augmented data agents rely on tool outputs for analytical decisions. Yet successful execution can return plausible but incorrect evidence, requirin

agentsarxiv-cs-ai

30 Sept 2026

Advancing Video-Text Pretraining with Multi-View Captions

arXiv:2609.35090v1 Announce Type: new Abstract: Video-text pretraining has achieved remarkable progress through the scaling of models and datasets, yet the quality of language supervision remains unde

Agents

AI-driven ionic liquid discovery with unified chemical intelligence

arXiv:2511.11257v2 Announce Type: replace-cross Abstract: The rational discovery of functional solvents remains challenging because macroscopic solvent behaviors emerge from complex many-body interact

agentsarxiv-cs-lg

Autonomous Research Project Management as an Agent Skill: A Case Study in Exact Spectral Spatial Regression

arXiv:2609.31683v1 Announce Type: new Abstract: This work presents an end-to-end demonstration of autonomous machine learning research conducted by an agent skill on consumer hardware. The demonstrati

Binding Multiple Modalities via Multimodal Wasserstein Barycenter

arXiv:2609.33800v1 Announce Type: new Abstract: Multimodal learning beyond two modalities commonly leverages a specific modality (e.g., text) to bind other modalities. However, how to establish a more

Can Motion-Language Models Ground Structure? STRIDE for Evaluating the Evaluators

arXiv:2609.32462v1 Announce Type: new Abstract: Motion-language models are typically scored by motion-language evaluators, but how well these evaluators ground language structure remains unclear. Here

Clinical Trajectory Alignment for Medical Vision-Language Pre-training

arXiv:2609.34439v1 Announce Type: new Abstract: Medical vision-language pre-training largely follows a visit-level image-report matching paradigm, aligning paired images and reports at individual visi

safetyarxiv-cs-cv

Contrast Matters: Understanding Robustness of In-Context Fine-Tuning to Target-Context Relatedness

arXiv:2604.01601v2 Announce Type: replace Abstract: In-context fine-tuning (IC-Train), training an LLM with labeled examples in-context, is increasingly used in place of standard fine-tuning for domai

ConvCue: Complementary Visual Inductive Biases for Vision-Language Models

arXiv:2609.34196v1 Announce Type: new Abstract: Modern vision-language models (VLMs) achieve strong performance across a broad range of multimodal tasks, yet still struggle with visual questions that

Disentangling Lung-Cancer CT/LDCT AI: A Systematic Evidence Map of Clinical Tasks, Evidence Chains, and Translational Gaps

arXiv:2609.35240v1 Announce Type: new Abstract: Artificial-intelligence studies using computed tomography (CT) for lung cancer are often broadly labelled 'prediction' despite addressing clinically dis

DynamicDx: Evaluating Evidence Acquisition in Video-Based Diagnosis

arXiv:2609.32957v1 Announce Type: new Abstract: Diagnosing a patient from video requires more than recognizing the sign: a vision-language model must turn what it sees into hypotheses, questions and t

Elastic Selective Spectral Hybrids for Train-Once, Export-Many Budgeted Inference

arXiv:2609.32486v1 Announce Type: new Abstract: Deploying a language model under different computing and latency budgets calls for compact models with different quality-cost trade-offs. Towards this e

Tutorials

Generative Uncertainty as a Self-supervised Signal for Semantic Similarity Learning

arXiv:2609.35341v1 Announce Type: new Abstract: Evaluating semantic similarity between videos is a fundamental challenge in computer vision, essential for tasks ranging from out-of-distribution (OOD)

tutorialsarxiv-cs-cv

HPMD: A Historical Persian Manuscript Dataset for Word Spotting with Line-Level Annotation

arXiv:2609.34490v1 Announce Type: new Abstract: Large collections of historical Persian manuscripts have been digitized, but searching them is still slow and mostly manual. Historians usually want to

safetyarxiv-cs-cv

Identifying Temporal Features within Transcoders for Time Sensitive Factual Recall

arXiv:2609.33183v1 Announce Type: cross Abstract: Large Language Models (LLMs) suffer from temporal misalignment, often due to the contradictory nature of their training corpora. While current mitigat

Intuition vectors

arXiv:2609.32619v1 Announce Type: new Abstract: Large self-supervised vision models learn representations that support scene segmentation and the semantic decomposition of physical objects. We ask whe

safetyarxiv-cs-lg

JazzSAMBA: A Synchronous and Asynchronous Multi-take Band Audio Dataset of Jazz Standards for Live Music Models

arXiv:2609.34931v1 Announce Type: cross Abstract: Machine learning has made strong progress on music tasks, both as assistive tools and as creative partners. However, most systems train on multitrack

Just-In-Time Agent Memory with Runtime Agentic Research

arXiv:2609.34385v1 Announce Type: cross Abstract: Memory is critical for AI agents. Many existing agent-memory systems follow an Ahead-of-Time (AOT) design, constructing memory before a specific reque

safetyarxiv-cs-lg

Just MLPs: Efficient Visual State Reconstruction for Multimodal Language Models

arXiv:2609.34972v1 Announce Type: new Abstract: Long visual token sequences often account for a substantial fraction of the computational overhead in multimodal large language models~(MLLMs). Existing

Learning Transferable Sensor Models via Language-Informed Pretraining

arXiv:2603.11950v2 Announce Type: replace-cross Abstract: Multimodal language models have demonstrated strong semantic understanding and reasoning over physiological and behavioral signals captured fr

safetyarxiv-cs-lg

Long Time No See: Benchmarking VLMs for Out-of-Sight Spatiotemporal Reasoning in Egocentric Videos

arXiv:2609.34630v1 Announce Type: new Abstract: Real-world AI systems must reason about objects that are no longer visible: an AR assistant guiding a user back to an object used earlier, a household r

Memory as a cache: Exact context reuse and deletion by construction

arXiv:2609.32395v1 Announce Type: cross Abstract: The KV cache of a transformer entangles every token's representation with its entire prefix: a passage encoded once cannot be reused under a different

MetaSampling: Making Frame Samplers Efficient for Long-Video Question Answering

arXiv:2609.33998v1 Announce Type: new Abstract: Frame selection is an important component of long-video question answering (VQA) with Multimodal Large Language Models (MLLMs). Existing frame-selection

Tutorials

Metro-WM: Long-Horizon Latent Planning with Realisable Sub-Goals

arXiv:2609.31868v1 Announce Type: cross Abstract: Model-predictive control with Joint-Embedding Predictive Architectures (JEPAs) provides a strong zero-shot goal-reaching planner, but it is only effec

tutorialsarxiv-cs-ro

MM-VeriRec: Failure-Guided Fusion for Verifiable Agentic Multimodal Recommendation

arXiv:2609.31718v1 Announce Type: cross Abstract: Images often carry recommendation constraints that text metadata only hints at. A movie may need to look dark, a product may need a minimal style, and

Multimodal LLMs Outperform Pathology Foundation Models in Cross-Domain Histological Similarity

arXiv:2609.32876v1 Announce Type: new Abstract: State-of-the-art pathology foundation models, trained on millions of histology tiles, can fail to preserve tissue similarity when comparisons cross slid

PQ-HSA: Reusing Product-Quantized Scores for Hybrid Sparse-Approximate Attention

arXiv:2609.33746v1 Announce Type: new Abstract: At each decoding step a language model attends over the key-value (KV) cache of every earlier token, so at long context the attention call is bounded by

QSCP: Beyond Class-Name Prompts for Query-Guided Semantic Change Parsing

arXiv:2609.33088v1 Announce Type: new Abstract: Traditional change detection (CD) identifies changes between bi-temporal remote sensing images, while semantic change detection (SCD) assigns predefined

Re:Cognize -- Open-Set Comic Character Re-Identification

arXiv:2609.34032v1 Announce Type: new Abstract: A manga reader meets a character on one page and knows them on sight a hundred pages later, without ever being handed a cast list. Re-identifying comic

RoboIRGBench: Benchmarking Implicit Referential Grounding in Vision-Language-Action Models

arXiv:2609.34384v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown strong capabilities in robotic manipulation, yet existing benchmarks typically assume that task-relevan

SAGE: Symbolic Action-Gating and Editing for LLM Task Planners

model-releasesarxiv-cs-ro

arXiv:2609.34268v1 Announce Type: new Abstract: Large language models (LLMs) are now the default cognitive core of embodied household agents, yet the plans they emit are rarely checked against a groun

Hardware

SANTA++: Sampling Attention through Representative Keys

arXiv:2609.35629v1 Announce Type: new Abstract: Attention often concentrates on a small subset of tokens in the context, but which subset matters changes from one query to the next. To exploit this ch

hardwarearxiv-cs-lg

Agents

SegBanana: Steering Unified Multimodal Models into Medical Segmenters

arXiv:2609.34235v1 Announce Type: new Abstract: Medical image segmentation remains challenging in practical deployment, as models often struggle to generalize beyond the distributions covered by their

agentsarxiv-cs-cv

Self-Evolving Time-Series Forecasting Agents with Episodic Memory and Online Policy Learning

arXiv:2609.32689v1 Announce Type: new Abstract: LLM-based agents are increasingly used for time-series forecasting because they can organise contextual information, perform multi-step analysis, and gu

Semantic Purification for Conditional Representation Learning

arXiv:2602.05464v2 Announce Type: replace-cross Abstract: Conditional representation learning aims to extract criterion-specific features for customized tasks. Recent methods construct conditional sub

Shallow Queries, Mature Values: Depth-Asynchronous Self-Speculation for Looped Transformers

arXiv:2609.34538v1 Announce Type: new Abstract: Looped Transformers reuse a shared block across recurrent depths, making autoregressive decoding expensive because every generated token requires many s

Hardware

Single-Layer MeMo as a Randomized Hamming-Kernel Classifier

arXiv:2609.34562v1 Announce Type: new Abstract: MeMo (Zanzotto et al., 2025) is a recent language-model architecture that stores associations between token contexts and next tokens in a correlation ma

hardwarearxiv-cs-lg

SketchSSM: Write to the Full State, Read from a Compact Sketch

arXiv:2609.33051v1 Announce Type: new Abstract: Hybrid-attention models replace most softmax attention layers with linear attention, reducing KV-cache growth and enabling larger decode batches where r

SkillPE: Creativity-Oriented Cinematic Skill Evolution for Text-to-Video Prompt Engineering

arXiv:2609.34335v1 Announce Type: new Abstract: Achieving high-quality, cinematic results in text-to-video generation remains challenging for non-experts, whose prompts often lack professional narrati

Stashbird: Efficient Speaker-Indexed Memory for Conversational Agents

arXiv:2609.34242v1 Announce Type: cross Abstract: AI agents require memory that preserves information across user-agent exchanges, user-to-user conversations, and group conversations with or without a

SubjectAnchor: Subject-Aware Memory-to-Video for Multi-Shot Storytelling

arXiv:2609.34502v1 Announce Type: new Abstract: We present SubjectAnchor, a Subject-Aware Memory-to-Video paradigm for multi-shot storytelling in which the current shot is generated by conditioning on

Applications

Task-Oriented Communications for Edge-Assisted Multi-View Localization

arXiv:2609.35173v1 Announce Type: cross Abstract: Unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) often lose satellite positioning in urban canyons, indoor facilities, and jammed o

applicationsarxiv-cs-ro

Theoretical Refinement of CLIP by Utilizing Linear Structure of Optimal Similarity

arXiv:2510.15508v2 Announce Type: replace Abstract: In this study, we propose an enhancement to the similarity computation mechanism in multimodal contrastive pretraining frameworks such as CLIP. Prio

What Can a Leaderboard Certify? Compositional Controllability for Fair Evaluation and Training of Biomedical Literature-Review Agents

arXiv:2609.32318v1 Announce Type: new Abstract: Leaderboards rank long-horizon agents by their final outputs. Yet a higher score alone does not establish whether two systems are comparable or which st

When Does Structured Knowledge Help Neural Theorem Proving?

arXiv:2609.34460v1 Announce Type: cross Abstract: Does structured mathematical knowledge help LLMs prove theorems in Lean 4? If so, for which models, and does the answer vary by problem? Formal librar

Hardware

WorldAttention: An Efficient Attention Architecture for Interactive Video World Models

arXiv:2609.34606v1 Announce Type: new Abstract: Leveraging the paradigm of autoregressive diffusion, text-conditioned interactive video world models aim to simulate temporally coherent environments gu

hardwarearxiv-cs-cv