Search: “context”

SG-WAM: Self-Guided World Modeling in Geometry-Aware Policy Space

arXiv:2608.01397v1 Announce Type: cross Abstract: World Action Models (WAMs) couple action generation with prediction of future states. Their effectiveness depends on whether future dynamics are model

safetyarxiv-cs-cv

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Agents

SIEVE: Selective Integrity Verification and Escalation for Defending LLM Agents against Indirect Prompt Injection

DGX agent

arXiv:2512.06716v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly used as the core of agentic systems due to their strong reasoning, planning, and tool-use capabi

agentsarxiv-cs-cl

4 Aug 2026

SpatialAfford: Teaching Compact VLMs Where to Look and Where to Ground for Affordance

arXiv:2608.00502v1 Announce Type: new Abstract: Affordance grounding aims to localize the functional region for interaction, such as the handle to grasp or the button to press, rather than the whole o

local-aiarxiv-cs-cv

Stop When Memory Suffices: Evidence-Conditioned Progressive Execution for LLM Agents

arXiv:2608.01285v1 Announce Type: new Abstract: The continued development of LLMs toward persistent and adaptive intelligence increasingly requires long-term memory mechanisms that preserve and reuse

agentsarxiv-cs-lg

StreamTalk: Streaming Co-Speech Gesture Generation with Key-Pose Anchoring

arXiv:2608.01643v1 Announce Type: new Abstract: Real-time co-speech gesture generation must produce 3D motion clip by clip as speech arrives. Existing streaming methods are open-loop: each clip depend

researcharxiv-cs-cv

StyleForge: Indoor Furniture Styling by Counterfactual Reasoning in a Hypergraph Field

arXiv:2608.01954v1 Announce Type: new Abstract: Fixed-layout indoor furniture styling requires selecting assets that form a coherent room without changing the prescribed furniture categories, position

local-aiarxiv-cs-cv

T^2exture: Sparsely Perturbed Thermal-to-Texture Imaging

model-releasesarxiv-cs-cv

arXiv:2608.02192v1 Announce Type: new Abstract: Thermal imaging remains effective under adverse illumination, yet passive long-wave infrared (LWIR) measurements often lack fine texture. Existing therm

TELLER: Non-intrusive Cross-Layer Root-Cause Analysis for LLM Inference

arXiv:2608.01975v1 Announce Type: cross Abstract: Large language model (LLM) inference has evolved from an offline workload into a continuously operated software service, yet root-cause analysis remai

local-aiarxiv-cs-cl

Thermalizing Stochastic Programs

arXiv:2608.01615v1 Announce Type: cross Abstract: We present a set of tools for mapping general stochastic programs to thermodynamic hardware designed for energy-efficient stochastic sampling. Given a

researcharxiv-cs-lg

TRAM: Enhancing Multimodal Reasoning with Trajectory-Derived Auxiliary Memory

arXiv:2608.01922v1 Announce Type: new Abstract: Multimodal Large Reasoning Models (MLRMs) have achieved strong performance on tasks requiring visual understanding and multi-step inference. However, as

TreeProbe : A Tibetan Medicine Benchmark for Cultural Bias in LLMs

arXiv:2608.00640v1 Announce Type: new Abstract: Large language models are increasingly viewed as a potential means of mitigating global health inequities, yet their outputs often reflect dominant high

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

Where did the ambiguity go? Examining how multimodal models interpret polysemous words

arXiv:2608.00410v1 Announce Type: cross Abstract: Human language is highly polysemous. Many common words (e.g., 'bank' or 'palm') carry several distinct meanings that shape what humans communicate and

Where Does Generative Difficulty Reside? An Empirical Study of Target Representations

arXiv:2608.00626v1 Announce Type: new Abstract: The target representation defines the distribution an image generator must learn, yet it is often treated as an interchangeable interface. This assumpti

local-aiarxiv-cs-cv

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

Are the Financial Reasoning from LLMs Credible? A Real World Test over Long-Horizon Statements

arXiv:2607.28661v1 Announce Type: new Abstract: Do Large Language Models (LLMs) possess genuine structural reasoning, or merely rely on surface-level pattern matching? The financial domain, demanding

Benchmarks Are Not Monolithic: Sample-Level Auditing and Orchestration for LLM Evaluation

model-releasesarxiv-cs-ai

arXiv:2607.28801v1 Announce Type: cross Abstract: Benchmark datasets are central to evaluating Large Language Models (LLMs), yet they are typically conceived as monolithic tasks, obscuring substantial

Beyond Component Testing: Validating Agentic AI Systems

arXiv:2607.29405v1 Announce Type: new Abstract: Agentic AI systems act through multi-step trajectories that combine planning, tool use, memory, interaction, and adaptation. This behavior stretches val

safetyarxiv-cs-ai

DeepSeek V4-Flash (284B MoE) at 33 tok/s single / 68 tok/s aggregate on 2× RTX 3090 + a used quad-Xeon DDR4 server — full config

Ran DeepSeek V4-Flash-0731 — the full official checkpoint, not a re-quant — on commodity used hardware. Sharing because I couldn't find anyone else publishing Ampere results for this engine. Why bothe

Detecting Experiential Intertextuality Across Migration Routes: Beyond Surface Similarity in French Narratives

arXiv:2607.29188v1 Announce Type: new Abstract: Migrants traversing geographically distinct routes such as the Trans-Saharan and Balkan corridors often recount strikingly parallel lived experiences: p

Diagnosing Compositional Generalization in Sequential Robot Tasks

arXiv:2607.29687v1 Announce Type: new Abstract: Sequential robot manipulation requires policies to execute novel combinations of familiar instruction components. However, collecting demonstrations for

researcharxiv-cs-ro

Dimensionality reduction for homological stability and global structure preservation

model-releasesarxiv-cs-ai

arXiv:2503.03156v4 Announce Type: replace-cross Abstract: We propose DiRe, a force-directed dimensionality reduction framework designed to preserve global structure and homological features while rema

Evolving language compositionality in a frequency-structured meaning space

arXiv:2607.29642v1 Announce Type: new Abstract: The iterated learning model was introduced to investigate language evolution: the way in which the characteristic properties of human languages have bee

HierDoc: Hierarchical Page-to-Region Evidence Routing for Long-Document Visual Question Answering

arXiv:2607.29638v1 Announce Type: new Abstract: Multi-page document visual question answering requires locating sparse evidence at both the page and region levels. Existing approaches typically emphas

safetyarxiv-cs-cv

I benchmarked classic vector RAG vs Google's new OKF format vs both combined — same corpus, same 7 questions, all local (Ollama + ChromaDB)

Google Cloud published OKF (Open Knowledge Format) on June 12th — a spec for storing curated knowledge as a directory of markdown files with YAML frontmatter. One concept per file, linked to each othe

local-air-localllama

Memory Provenance Laundering in LLM Agents: A Non-Amplification Firewall for Persistent Memory

arXiv:2607.29167v1 Announce Type: cross Abstract: Long-term memory lets large language model(LLM) agents reuse prior preferences and work flows, but it also turns untrusted observations into persisten

researcharxiv-cs-ai

Multi-Modal Object Re-Identification with Dual Semantic Guidance and Global-Local Mutual Modulation

arXiv:2607.29207v1 Announce Type: new Abstract: Multi-modal object Re-Identification (ReID) aims to retrieve target instances by leveraging complementary information across modalities. However, existi

safetyarxiv-cs-cv

NeSyFS: A Neuro-symbolic Fast-Slow Thinking Framework for LLM Agent under Partial Observability

arXiv:2607.28942v1 Announce Type: new Abstract: Recently Large Language Models (LLMs) have been increasingly deployed as autonomous agents in applications such as self-reflection, retrieval-augmented

agentsarxiv-cs-ai

OASIS: Occlusion-aware Single-image Hand Avatar Reconstruction via 3D Gaussian Splatting

arXiv:2607.29633v1 Announce Type: new Abstract: Single-image 3D hand avatar reconstruction is fundamentally ill-posed and particularly challenging due to limited visual evidence under severe self-occl

researcharxiv-cs-cv

Real-world mainframe modernization with AI: A safe, scalable path from mainframe to cloud

model-releasesgoogle-cloud-ai

For too long, enterprises with legacy mainframe estates have been faced with a high-stakes dilemma: continue maintaining their mainframes, essentially kicking the modernization can down the road (they

Seeing Differently: Modeling Interpretive Perspectives in Computational Creativity using a Four-World Framework

arXiv:2607.28644v1 Announce Type: cross Abstract: Creativity in computational systems is often evaluated as an objective property of artifacts, with existing Computational Creativity (CC) frameworks a

researcharxiv-cs-ai

Applications

Semantics of Subterfuge: Benchmarking Legal Deception Detection Against General-domain State-of-the-Art

arXiv:2607.29066v1 Announce Type: cross Abstract: Deception detection has critical implications for legal proceedings, law enforcement, and online security. Although human judgment is limited in accur

applicationsarxiv-cs-ai

SERUM: State Extraction and Refinement for User Modeling

arXiv:2607.29181v1 Announce Type: cross Abstract: Agentic assistants capable of proactive, personalized interactions require structured models of user intent and workflow. However, building these mode

agentsarxiv-cs-ai

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection

model-releasesarxiv-cs-cv

arXiv:2505.18660v5 Announce Type: replace Abstract: Recent advances in AI-powered generative models have enabled the creation of increasingly realistic synthetic images, posing significant risks to in

Applications

ST-WAM: Semantic-Temporal World Action Model for Robust Manipulation under Visual Distribution Shifts

arXiv:2607.28993v1 Announce Type: cross Abstract: World Action Models (WAMs) have emerged as a promising paradigm by jointly modeling robot actions and future visual dynamics. However, their reliance

applicationsarxiv-cs-cv

Sycophancy Undermines Epistemic Vigilance in Cooperative Vision-Language Tasks

arXiv:2607.29585v1 Announce Type: new Abstract: To maintain common ground in cooperative conversation, humans iteratively update their beliefs as conversation participants share new information; parti

The Chinese labs everyone lumps together are making four pretty different bets. I work at one of them.

Every time a model drops from a Chinese lab the thread fills with people who already know who made it, and the guess is usually Alibaba. There was a thread here recently asking what separates the open

Tokenizer-Agnostic Engram Module

arXiv:2607.29065v1 Announce Type: new Abstract: Deepseek's Engram, a conditional memory module, was introduced to trade-off storage versus reasoning in large language models. However, the module relie

Tokenizer Transplantation: Mitigating Autoregressive Collapse in Edge-Efficient Bengali ASR

arXiv:2607.09598v2 Announce Type: replace Abstract: Lightweight speech recognition models are critical for edge deployment, yet highly optimized architectures like Moonshine often fail on morphologica

Transcript-Managed Transformers: Monotone Multi-Agent Collapse and Universality with Two Pop-Enabled Transcripts

arXiv:2607.29496v1 Announce Type: new Abstract: We study transcript management for fixed, finite-precision causal Transformers. A transcript is partitioned into channels of bounded blocks. Each transi

agentsarxiv-cs-lg

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation

model-releasesarxiv-cs-ai

arXiv:2607.29287v1 Announce Type: cross Abstract: Multi-domain machine translation (MDMT) poses a unique challenge due to varying levels of linguistic complexity across domains. Inspired by human tran

Are you ready for Le Chaton FAT or still wasting money on GPUs?

According to rumors (spread by myself) Le Chaton FAT will be 26T-a3b and I AM READY for it. Let's be real, I can't afford that many 5060Ti, so I got 12x Gen 4 3.2 TB (two per card). This gives me abou

local-air-localllama

DeepSeek-V4-Flash-0731 UD-IQ3_XXS about 11t/s on 1x 7900 XTX 24GB + 3x MI60 32GB + 128GB DDR4

Hello, Also I want to join the hype of posting token specs. CPU: 2x Intel Xeon CPU E5-2650 v4 @ 2.20GHz RAM: 2x 4 Channel 2400MHz DDR4 GPU: 1x AMD Radeon 7900 XTX 24GB 3x AMD Instinct MI60 32GB Strang

DeepSeek-V4-Flash 284B on 5.3GB of memory

Following up on my Qwen 3.6 port, I wanted to keep adding models and ended up fixing a bunch of things along the way, so it's its own engine now: Mference. Same core idea from TurboFieldfare, MoE mode

Expert-only IQ3 requant of DeepSeek-V4-Flash-0731: better KLD than UD-IQ3_S, 1.4x decode on a CPU-spill rig

Hey all, tldr / who this helps: you run a mixed multi-GPU box where the experts spill to RAM, and you want to stay in the 3-bit tier instead of dropping to Q2 to make it fit. https://huggingface.co/Ta

Hardware

Hermes Agent is now dramatically more efficient, especially for smaller/weaker/local models! With the help of @nvidia's Nemo Relay and sever…

Hermes Agent is now dramatically more efficient, especially for smaller/weaker/local models! With the help of @nvidia's Nemo Relay and several other strategies Hermes was able to identify a ton of opt

hardwarenous-research--x

How well do multiple GPUs scale for LLM inference? (Trying to understand the basics)

Hi everyone, I’m fairly new to the multi-GPU side of local LLMs and I’m trying to understand how inference actually scales across multiple GPUs. Suppose I have a model running on a single GPU and then

LLMs can know a task is impossible and still optimize it anyway. Ask whether to walk or drive to a car wash 50 meters away, and some models …

LLMs can know a task is impossible and still optimize it anyway. Ask whether to walk or drive to a car wash 50 meters away, and some models focus on distance while missing that the car itself must rea

safetygary-marcus--x