Search: “context”

Which Metadata Matters for LLM Tool Selection in MCP? Evidence from Controlled Factor-Level Interventions

arXiv:2610.14334v1 Announce Type: new Abstract: In Model Context Protocol (MCP) systems, LLMs select tools from metadata rather than from their implementations. Names and descriptions summarize what a

15 Oct 2026

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Hardware

BELT : BEhavior-Aligned Low-Rank KV Cache Compression with Learned Top-k Rank Allocation

DGX agent

arXiv:2610.17966v1 Announce Type: new Abstract: Long-context inference makes the key-value (KV) cache a major memory bottleneck for large language models. We propose BELT, a low-rank KV cache compress

hardwarearxiv-cs-lg

14 Oct 2026

Building Trustworthy Household Robots through Open-World Safety

arXiv:2610.14034v1 Announce Type: new Abstract: Foundation models are expanding robot capabilities, enabling robots to handle more diverse objects, follow sophisticated instructions, and operate in co

safetyarxiv-cs-ro

Tutorials

Characterizing the Separability Gap in Prior-Data Fitted Networks

arXiv:2610.14989v1 Announce Type: new Abstract: Prior-data fitted networks (PFNs) are transformers pretrained on simulated datasets to approximate Bayesian posterior predictive distributions. Standard

tutorialsarxiv-cs-lg

ChronoScribe: Semantic-Numerical Specialization for Instruction-Driven Time Series Forecasting

model-releasesarxiv-cs-lg

arXiv:2610.16345v1 Announce Type: cross Abstract: Recent advances in instruction-driven time series forecasting highlight a fundamental tension: systems must simultaneously master natural-language ins

Dependency Reasoning for Aspect Sentiment Quadruple Prediction

arXiv:2610.14873v1 Announce Type: cross Abstract: Aspect Sentiment Quadruple Prediction (ASQP) is fundamentally a relational reasoning problem: identifying aspect-opinion-category-sentiment quadruples

researcharxiv-cs-lg

GIFT: Global Irreplaceability Frame Targeting for Efficient Video Understanding

arXiv:2603.25072v2 Announce Type: replace Abstract: Video Large Language Models (VLMs) have achieved remarkable success in video understanding, but the significant computational cost from processing d

researcharxiv-cs-cv

Kwai Summary Attention V2 Technical Report

arXiv:2610.18654v1 Announce Type: new Abstract: Summary-token architectures such as Kwai Summary Attention (KSA) compress distant context into learnable Summary token per chunk, and hybrid variants in

researcharxiv-cs-lg

Tutorials

Learning Source Structure: Bayesian Prediction with Transformers

arXiv:2610.18725v1 Announce Type: new Abstract: A transformer trained on sequences whose source parameters are drawn afresh each time can learn only what the sequences share: the source family and its

tutorialsarxiv-cs-lg

Learning Transferable World-Action Models from Task-Paired Human Videos

arXiv:2610.14351v1 Announce Type: new Abstract: World-action models inherit broad visual and physical priors from video pre-training. However, standard within-video next-frame prediction allows them t

safetyarxiv-cs-cv

Observe, Share, or Predict? Disentangling Partner Information in Embodied Multi-Agent Collaboration

model-releasesarxiv-cs-ro

arXiv:2610.16895v1 Announce Type: cross Abstract: LLMs are used as high-level controllers for embodied agents, but it remains unclear whether they support collaborative reasoning, such as anticipating

On the Dynamics of Delayed Generalization in Linear Models

arXiv:2602.08302v2 Announce Type: replace Abstract: Delayed generalization, where training accuracy becomes nearly perfect substantially before test accuracy, has often been studied in the context of

safetyarxiv-cs-lg

Pessimistic Latent Task-aware Optimization for Robust Offline Meta-Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2610.15428v1 Announce Type: new Abstract: Context-based offline meta-reinforcement learning (COMRL) has advanced almost entirely through better task representations, which separate task identity

Local Ai

Physics-Informed Graph Neural Networks to Reconstruct Local Fields Considering Finite Strain Hyperelasticity

arXiv:2507.05291v2 Announce Type: replace Abstract: We propose a physics-informed machine learning framework called P-DivGNN to reconstruct local stress fields at the micro-scale, in the context of mu

local-aiarxiv-cs-lg

PRISM: Precision Forcing for Generalist Vision-Language-Action Policies

arXiv:2610.14704v1 Announce Type: new Abstract: Coupling a pretrained vision-language model (VLM) with a diffusion or flow-matching action expert has become the mainstream vision-language-action (VLA)

safetyarxiv-cs-ro

Tutorials

RM-WAM: Reliable Memory-Augmented World Action Models for Long-Horizon Robot Manipulation

arXiv:2610.15305v1 Announce Type: new Abstract: World Action Models (WAMs) improve robotic manipulation by jointly predicting future visual states and actions, yet most existing methods make decisions

tutorialsarxiv-cs-ro

SPROUT: Scaling Agentic Reinforcement Learning for Long-Horizon Software Engineering

arXiv:2610.14405v1 Announce Type: cross Abstract: Reinforcement learning (RL) has driven substantial progress in coding agents by relying on verified successful trajectories as learning signals. Howev

safetyarxiv-cs-lg

Strata performance finetuning - try it out

As strata is somewhat new, I assume that some people din't yet learn how to finetune it for best performance on their machine. I find documentation a bit hard to navigate (use your agents for this!),

Hardware

Swarm Telepathy: Prefill-Free KV-Cache Transfer Across Families

arXiv:2610.15095v1 Announce Type: new Abstract: LLM multi-agent systems split work across agents that communicate through text. An agent summarizes its findings, another agent receives the text. This

hardwarearxiv-cs-lg

Text-Only vs. Image-Aware VLM Judges for Manga Translation Evaluation

arXiv:2610.17908v1 Announce Type: cross Abstract: In manga translation, visual context outside speech-bubble text, including speaker identities, referents, and scene tone, is depicted in page images,

researcharxiv-cs-cv

VETime: Vision Enhanced Zero-Shot Time Series Anomaly Detection

arXiv:2602.16681v2 Announce Type: replace Abstract: Time-series anomaly detection (TSAD) requires identifying both immediate Point Anomalies and long-range Context Anomalies. However, existing foundat

safetyarxiv-cs-cv

What Can Language Models Inherit from Solomonoff Induction? Limits, Attainable Properties, and What Served Conditionals Reveal

model-releasesarxiv-cs-lg

arXiv:2610.14007v1 Announce Type: new Abstract: A familiar line of reasoning runs as follows: language models are flexible approximators trained under a strictly proper loss, so scale brings them clos

When Dynamic Scaling Fails: A Scale-State Feedback Governs Recurrent-State Quantization in Linear-Attention and SSM LLMs

arXiv:2610.15139v1 Announce Type: new Abstract: Linear-attention and state-space LLMs carry long context in a fixed-size recurrent state, and quantizing that state is the natural way to cut its cost d

researcharxiv-cs-lg

Tools

GitHub’s model for secret detection: Finding more secrets with less noise

GitHub’s context-aware secret classifier improves detection quality, raises weighted acceptance by 11.5%, and reduces median scan execution time by 86%. The post GitHub’s model for secret detection: F

toolsgithub-ai-blog

LiquidAI/LFM2.5-24B-A2B

Gguf's: https://huggingface.co/LiquidAI/LFM2.5-24B-A2B-GGUF Free Demo: https://playground.liquid.ai 'LFM2.5-24B-A2B is a 24B-parameter reasoning model with only 2B active parameters, built for fast, p

Agents

router lives in the harness, not a gateway, bc the harness knows the task blog: https://www.langchain.com/blog/how-to-build-a-model-router-i…

router lives in the harness, not a gateway, bc the harness knows the task blog: https://www.langchain.com/blog/how-to-build-a-model-router-in-the-harness https://x.com/neil_xbt/status/2109979966859510

agentsharrison-chase--x

Industry

Spranic builds spatial memory for physical AI

Physical AI needs context about its surroundings to adapt beyond a fixed set of instructions. Munich-based Spranic is building a spatial memory layer that records physical spaces and how they change.

industrysiliconangle

AutoIndexer: Flexible-Order Decoding by Training Causal Models on Chains of Edits

arXiv:2610.12545v1 Announce Type: cross Abstract: Autoregressive decoding is less suited to non-causally ordered data, e.g., cross-references or future dependencies, since their outputs cannot be revi

researcharxiv-cs-ai

BLiMPPI: Benchmark of Linguistic Minimal Pairs for Polarity Items

model-releasesarxiv-cs-cl

arXiv:2610.13607v1 Announce Type: new Abstract: Negative polarity items (NPIs), such as 'anymore' and 'ever', are grammatical only in select environments, predominantly in the context of negation. Bec

COFFEQA: Counterfactual-Guided Few-Shot Distillation for LLM Question Answering

arXiv:2610.12837v1 Announce Type: cross Abstract: Knowledge distillation aims to train a smaller student model to mimic a larger teacher model for resource-constrained environments. However, the proce

researcharxiv-cs-ai

Collaborative Learning and Reasoning over Model Slices

arXiv:2610.12927v1 Announce Type: new Abstract: Large language models (LLMs) excel across diverse tasks, benefiting from knowledge priors, in-context reasoning, and test-time computation. Despite thes

ManeuverFlow: Maneuver Hypothesis Generation with Future Evidence for Trajectory Evaluation and Refinement in End-to-End Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2610.13409v1 Announce Type: new Abstract: End-to-end planning in complex scenes must model diverse driving intentions and select the most appropriate trajectory using scene context and future ri

Proactive Agentic Orchestration

arXiv:2610.13485v1 Announce Type: new Abstract: Agentic orchestration delegates tasks to sub-agents with independent contexts, providing a key path to extending the effective execution horizon of larg

safetyarxiv-cs-cl

Retrieval-Augmented Multimodal Language Model with Heterogeneous Evidence Integration for Clinical Prognosis

arXiv:2610.13510v1 Announce Type: new Abstract: Clinical prognosis requires integrating structured measurements, physiological waveforms, longitudinal history, and population context. We introduce PRI

Hardware

Tabular Foundation Models Are Effectively Shallow

arXiv:2610.13253v1 Announce Type: cross Abstract: In-context-learning Tabular Foundation Models (TFMs) are uniquely suited to scenarios with limited resources or privacy constraints, as they solve new

hardwarearxiv-cs-ai

Time Delay System for Sequence Modeling

arXiv:2610.12864v1 Announce Type: new Abstract: Existing sequence models share a critical limitation: they lack an explicit, interpretable mechanism for content-aware temporal recall. LSTMs compress e

researcharxiv-cs-cl

UkrMeme: Multimodal Explainable Persuasion Detection in Ukrainian Memes

arXiv:2610.13783v1 Announce Type: new Abstract: Memes play a central role in modern online communication, especially in contexts of political conflict where visual and textual cues combine to convey p

Every Model That Can Be Run On 10-16GB VRAM Ranked

It's been 4 years since c.ai first hallucination model, and yet, we're nowhere good enough at LLMs in terms of spontaneity/interesting hallucination features. Fortunately, last year brought new archit

Gemma4 E4B EXL3 - Alternative to Llama.cpp on Jetson Orin

My Jetson Orin–optimized engine, little-gemma V1.0, substantially outperforms llama.cpp. Even after exhausting every practical GGUF option, however, it still falls short of the ideal performance level

Qwen3.8 Flash Next fixed my GNOME extension

I love Dash2Dock Lite, but Icedman is always a week or two before updates. I randomly ran pacman for the first time in weeks, not realizing GNOME had a major update. I told it to fix it in DeepSeek Ha

vllm-ascend updates (GLM5.3-flash) on dual 310p Ascend cards

Alright, I learend a few valuable lessons since I posted about a week ago, and I've made more strides with the DDR4x Ascend 96GB 310P cards I purchased, so here we go, meet the new friendly and less v

48Gb VRAM speed AND quality ! (Qwen 3.8 27B Swift 1.5 W8A16)

Hi, Because sometimes you need both speed AND quality, I made my own Qwen 3.8 27B Swift 1.5 quant. It's an 8 bits AWQ + GPTQ quant. Made with love and precision (read the model card) on my 4 RTX 3090,

I asked 3 Qwen 3.8 models to solve recent AtCoder problems at 4 thinking efforts

I was looking into finalizing my daily driver and it was not clear which one to chose. I have a 5060ti 16GB so I picked the following contenders, which seem to be working at a reasonable speed on my h

I have an ESC4000 G3 with 8x T4s in it - what is the fastest way I can deploy Qwen3.5-9B for about 10-15 users concurrently: currently using llama.cpp

Hi All: I have an Asus ESC 4000 G3 with 128 GB DDR4 RAM - I tried putting in my V620s but couldn’t put more than 2. Sadly, pivoted to T4s, these are 72 watt passive cards and I thought I could use the

Strata with Qwen3.8 Flash Next UD-Q4_K_XL

Been seeing quite a few posts about Strata lately, so I figured I'd give it a shot on my RTX PRO 6000 and I am very impressed. Most of the benchmarks I've seen are using IQ2 or IQ3 quants, so I wanted

AdaptEvo: Adaptive Agent Learning with Evolving Supervision

arXiv:2610.11354v1 Announce Type: new Abstract: Rule-governed contextual decision tasks require models to apply specified rules to case-specific context and evidence. Written rules can leave gaps in d

safetyarxiv-cs-cl

9 Oct 2026

Can Decision Models Understand Stance? Evaluating Jev Against General-Purpose LLMs

model-releasesarxiv-cs-cl

arXiv:2610.11901v1 Announce Type: new Abstract: Stance detection requires identifying an author's attitude toward a given target, sometimes based on conversational context. Jev, a specialized decision

9 Oct 2026

Evaluating Local Language Model Agents for Reproducible Data Engineering: An Empirical Software Engineering Study of Mobility Workflows

arXiv:2610.11482v1 Announce Type: cross Abstract: Context: Large language model (LLM) agents are increasingly used as software and data-engineering assistants, yet evidence about locally deployable op