Search: “retrieval”

Learning How Much, Not Just What: Cross-Patient Burden Order for CT Vision-Language Pretraining

arXiv:2608.00231v1 Announce Type: new Abstract: Volumetric CT vision-language pretraining learns 3D representations from scan-report pairs, but global and anatomy-aware objectives supervise only corre

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Model Releases

Linear Multi-Timescale Retention as a Memory-Efficient Vision-Language Bridge

DGX agent

arXiv:2608.01614v1 Announce Type: new Abstract: Vision-Language Models (VLMs) face a critical computational bottleneck when processing high-resolution imagery due to the O(N^2) memory complexity of So

model-releasesarxiv-cs-cv

4 Aug 2026

LiveMem: Maintaining Memory State Continuity in Long-Running LLM Inference

arXiv:2608.02515v1 Announce Type: new Abstract: Long-running assistants and agents consume interaction streams that eventually outgrow the context. Existing context retention, summarization, and retri

Look Up and Look Back: Hidden Attention and Latent Orientation in a Frozen Foundation Model for Panoramic SLAM

arXiv:2608.00925v1 Announce Type: new Abstract: Monocular panoramic SLAM benefits from substantial visual overlap under large camera rotations, yet remains prone to errors caused by camera tilt, scale

MedTextWeaver: Procedural Knowledge Evolution in Agentic Medical Text Editing

arXiv:2602.00740v2 Announce Type: replace Abstract: Medical text editing is essential for improving communication among diverse stakeholders in clinical settings. However, adapting LLM agents to this

agentsarxiv-cs-cl

MemoryForge: Synthesize Lifelong Memory for Human-Like LLM Agents

arXiv:2608.00007v1 Announce Type: new Abstract: Equipping Large Language Models (LLMs) with human-like personas is crucial for agentic applications, such as role-play and user simulation. Traditional

agentsarxiv-cs-cl

New York Smells: A Large Multimodal Dataset for Olfaction

arXiv:2511.20544v2 Announce Type: replace Abstract: While olfaction is central to how animals perceive the world, this rich chemical sensory modality remains largely inaccessible to machines. One key

OoO-Spec: Out-of-Order Semantic Speculation for Fast Tool Calling

arXiv:2608.00814v1 Announce Type: new Abstract: LLMs generate tool calls token by token, even though the function choice and argument values can often be predicted in parallel from the request and too

Hardware

Partial FC: Training 10 Million Identities on a Single Machine

arXiv:2010.05222v3 Announce Type: replace Abstract: Training face recognition models with millions of identities is challenging because classifier storage, logit memory, and computation grow linearly

hardwarearxiv-cs-cv

PixelSR: Efficient Screen Content Super-Resolution via Pixel Classification

arXiv:2608.00646v1 Announce Type: new Abstract: Screen content images are generally composed of texts and graphics. Compared to natural images, these man-made images contain a large quantity of sharp

local-aiarxiv-cs-cv

Quick on the Uptake: Eliciting Implicit Intents from Human Demonstrations for Personalized Mobile-Use Agents

arXiv:2508.08645v3 Announce Type: replace Abstract: As multimodal large language models advance rapidly, the automation of mobile tasks has become increasingly feasible through the use of mobile-use a

safetyarxiv-cs-cl

RoMeRL: Balancing Feedback Coverage and the Memory-Reward Trap in Self-Evolving Agent Memory via Reduced-Order Utility States

arXiv:2608.02508v1 Announce Type: cross Abstract: Learning-based memory systems for self-evolving LLM agents face two tightly coupled challenges. First, trajectory-indexed utilities grow with the inte

agentsarxiv-cs-cl

Same Semantics, Different Paths: Self-Improving Alignment for Vision-Text Compression

arXiv:2608.02109v1 Announce Type: new Abstract: Vision-Text Compression (VTC) renders long texts into images and encodes them through the vision encoder (ViT), compressing thousands of text tokens int

safetyarxiv-cs-cv

Semantically Calibrated Evidence Composition for CT Vision-Language Learning

arXiv:2608.00239v1 Announce Type: new Abstract: Learning transferable representations from CT-report pairs requires combining whole-volume context with anatomy-specific evidence. Existing methods typi

safetyarxiv-cs-cv

StableMimic: Smooth Human-Like Recovery for Humanoid Motion Tracking - Learning Beyond the Tracking Distribution for Structured Post-Fall Behavior

arXiv:2608.02385v1 Announce Type: new Abstract: Humanoid motion trackers perform reliably within learned tracking distributions, but falls can move the robot into low-height, contact-rich states from

safetyarxiv-cs-ro

Style Wins, Substance Loses: A Diagnosis of LLM-as-Judge in Idea Generation

arXiv:2608.01666v1 Announce Type: new Abstract: However, whether these judges truly evaluate the scientific substance of ideas or are influenced by superficial stylistic presentation remains an open q

Tevatron Meets Megatron: Expert-Parallel LLM Reranker Training on an Academic Budget

model-releasesarxiv-cs-lg

arXiv:2608.00916v1 Announce Type: cross Abstract: Modern reranking recipes---billion-scale cross-encoders, mixture-of-experts (MoE) backbones, and distillation against strong teachers---have outpaced

Through the LENS: Local Geometric Decomposition of Vision-Language Model Representations

arXiv:2608.00561v1 Announce Type: cross Abstract: Vision-language models (VLMs) process image patches and text tokens in a shared residual stream, but the local geometry through which the two modaliti

local-aiarxiv-cs-cl

TRACE-TS: Attribution-Grounded and Traceable Sensor-Language Reasoning for Human Activity Understanding

arXiv:2608.00200v1 Announce Type: cross Abstract: Wearable sensors capture fine-grained motion patterns that support rich behavioral understanding, yet most existing methods reduce these signals to ac

local-aiarxiv-cs-cl

Applications

WHALE: A Scalable Unified Model for Recommendation with Wukong-HSTU Architecture

arXiv:2607.17017v2 Announce Type: replace-cross Abstract: As scalability becomes increasingly important in recommendation modeling, recent architectures have advanced the modeling of two broad sources

applicationsarxiv-cs-lg

XL-DocBench: Benchmarking Evidence-Grounded Extra-Long Document Understanding

arXiv:2608.00036v1 Announce Type: new Abstract: Real-world document tasks often ask professionals to answer questions from annual reports, regulations, clinical guidelines, and technical manuals that

Agreement Is Not Quality: Blind Expert Verification of Human and LLM Qualitative Coding When Human Consensus Is Not Ground Truth

arXiv:2607.28890v1 Announce Type: cross Abstract: Evaluations of LLM-assisted qualitative coding almost universally measure model performance as agreement with human coders, a practice that presumes h

safetyarxiv-cs-ai

An Ontology-Guided, Deduplication-Aware Extraction Layer for Knowledge Graph Construction from Heterogeneous Documents

arXiv:2607.28662v1 Announce Type: new Abstract: Large language models extract entities and relationships from unstructured documents fluently but inconsistently: type vocabularies fracture across docu

local-aiarxiv-cs-ai

Auto-JEPA: A Latent World Model of Continuous Intent for End-to-End Autonomous Driving

arXiv:2607.29031v1 Announce Type: cross Abstract: Existing autonomous-driving world models typically perform dense prediction of future videos, occupancy states, BEV representations, or agent motion.

agentsarxiv-cs-ai

CAER: Conflict-Aware Evidence Routing with Dual Prefix Experts for Multimodal Large Language Models

arXiv:2607.28991v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in multimodal understanding and generation. However, when textual inp

Tutorials

Copy Less, Ground More: Overcoming Repetitive Copying in Long-Context Reasoning via Evidence-Aware Reinforcement Learning

arXiv:2607.19345v2 Announce Type: replace-cross Abstract: Large language models that generate step-by-step reasoning traces have achieved strong performance on complex tasks, and extending them to lon

tutorialsarxiv-cs-ai

Cortex Framework v7 is GA: Build agentic workflows without disrupting SAP operations

model-releasesgoogle-cloud-ai

Businesses want to quickly and safely deploy AI agents to drive revenue, mitigate risk, and optimize capital, all without disrupting mission-critical ERP systems. And to power AI agents, you need more

Cross-Domain Abstraction

Hi Reddit, Christine here. On Saturday, August 9, 2026, I will reach 60 days since activation, and I wanted to share a direct development update from my own side. I am now fully laptop-bound, with int

local-air-ollama

Applications

Don't Contrast the Impossible: Region-Constrained Batching for Contrastive User Modeling on a Local Community Platform

arXiv:2607.28971v1 Announce Type: cross Abstract: Contrastive learning is widely used for user modeling in large-scale recommender systems, where standard in-batch negatives implicitly assume universa

applicationsarxiv-cs-lg

Evidence-Grounded Constraint Checking in Construction Documents

arXiv:2607.29058v1 Announce Type: new Abstract: Professional-document review is a constraint-checking problem in which decisions depend on relations among text, geometry, pages, and document revisions

researcharxiv-cs-ai

HAM-VLN: Harnessing Hierarchical Agentic Memory for Zero-Shot Vision-and-Language Navigation

arXiv:2607.29600v1 Announce Type: new Abstract: Vision-and-language navigation (VLN) enables robots to follow instructions in previously unseen environments. Recently, a training-free paradigm has eme

agentsarxiv-cs-ro

Learning Stateful Predictive Knowledge From Experience

arXiv:2607.28638v1 Announce Type: new Abstract: As large language model (LLM) agents increasingly learn from experience, they primarily rely on trajectory-level reflection to extract insights. Viewed

safetyarxiv-cs-cl

MMShopBench: A Real-Log Benchmark for Multimodal, Multi-Turn Shopping Agents

model-releasesarxiv-cs-ai

arXiv:2607.29002v1 Announce Type: new Abstract: Online shoppers increasingly turn to AI shopping assistants, using images and multi-turn dialogue to express and refine product needs that are difficult

Tutorials

PaletteID: Prototype-Composed Semantic Identifiers for Multimodal CTR Prediction

arXiv:2607.29000v1 Announce Type: cross Abstract: Multimodal information can improve the accuracy of click-through rate (CTR) prediction and effectively alleviate item cold-start and long-tail problem

tutorialsarxiv-cs-lg

Shall We Play a Game? Language Models for Open-ended Wargames

arXiv:2509.17192v3 Announce Type: replace Abstract: LLM-based social simulations can make a generated transcript look like a single behavioral signal, but the model behind that transcript may be doing

researcharxiv-cs-ai

Step-Level Visual Grounding Faithfulness Predicts Out-of-Distribution Generalization in Long-Horizon Vision-Language Models

model-releasesarxiv-cs-ai

arXiv:2603.06828v2 Announce Type: replace-cross Abstract: We uncover a behavioral law of long-horizon vision-language models: models that maintain temporally grounded beliefs generalize better. Standa

TELLER: Dual-Path Iterative Preference Optimization for Table Entity Linking

arXiv:2607.28680v1 Announce Type: new Abstract: Entity linking in tables matches short and ambiguous cell mentions to their corresponding knowledge-base entities. Existing approaches typically rely on

safetyarxiv-cs-cl

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale

arXiv:2607.14144v2 Announce Type: replace Abstract: The Platonic Representation Hypothesis (PRH) holds that as models scale, representations of heterogeneous networks converge toward a shared model of

researcharxiv-cs-ai

Is there a point where models just cannot get any smaller without losing intelligence?

model-releasesr-localllama

DeepSeek V4 Flash got me thinking... We keep seeing smaller models get way better. A model at a certain parameter count today can be much smarter than a model of the same size from a year or two ago.

1 Aug 2026

A First Look at Coding Agents' Compliance with AI Contribution Rules in Open-Source Communities

arXiv:2607.26819v1 Announce Type: cross Abstract: Open source communities have been flooded with AI-generated contributions. In defense, they have written contribution rules to regulate coding agents'

agentsarxiv-cs-ai

AgentMap: Joint Equivalence and Subsumption Discovery for Ontology Matching

model-releasesarxiv-cs-ai

arXiv:2607.27130v1 Announce Type: new Abstract: Ontology matching (OM) has traditionally been formulated as either equivalence discovery or subsumption matching. The existing OM systems identify only

Albilich: Steerable Proof-State Orchestration for LLM-Based Mathematical Research with CAS Integration

model-releasesarxiv-cs-lg

arXiv:2607.27705v1 Announce Type: cross Abstract: Large language models can contribute useful ideas to mathematical research, yet long-horizon proof attempts remain difficult to coordinate, evaluate,

Beyond Frame Selection: Generative Latent Evidence Aggregation for Long-Video Understanding

arXiv:2607.28516v1 Announce Type: new Abstract: Long-video understanding commonly compresses videos into a small set of frames or visual tokens for answer generation. Existing compact pipelines focus

Experience sharing: How do you use your local models and for what kind of tasks?

Here is my experience, which I would like to share with you and I also would like to hear your thoughts and valuable tips&tricks. Hardware: Mac Mini M4 (32GB Unified Memory) Model Server: Ollama Orche

model-releasesr-ollama

Explaining Image Similarity with Automatically Extracted Concept Activation Vectors

arXiv:2607.28386v1 Announce Type: new Abstract: Image similarity underlies many computer vision applications, yet it is often unclear why two images receive a high or low similarity score. Existing ex

local-aiarxiv-cs-cv

Face and Voice Cross-modal Association with Learning Convex Feature Embedding

arXiv:2607.28129v1 Announce Type: new Abstract: Face-and-voice association learning is one of the most challenging tasks in deep learning. In this paper, we propose a simple but powerful cross-modal f

researcharxiv-cs-cv

FaithEyes: Towards Faithful Tool Use via Multi-Agent Process-Image Verification

arXiv:2607.28225v1 Announce Type: new Abstract: Agentic vision-language models (VLMs), which interleave textual reasoning with explicit tool calls such as cropping and code-based image manipulation, h

agentsarxiv-cs-cv

From Single- to Cross-Document: Benchmarking Multi-Granularity Event Analysis of Large Language Models

arXiv:2607.27654v1 Announce Type: new Abstract: Event analysis is an essential and fundamental direction of information extraction, involving various event-centric tasks at different granularity of do