Search: “context”

Benchmarking Code LLM-as-a-Judge via Constrained Perturbation and Calibration

model-releasesarxiv-cs-ai

arXiv:2512.20159v2 Announce Type: replace-cross Abstract: Code from LLM-assisted development may contain defects like API hallucinations, motivating the development of code evaluation metrics to asses

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Can LLMs Anticipate Their Cruxes?

DGX agent

arXiv:2610.21006v1 Announce Type: new Abstract: To use language models to help us make decisions we would like to understand the rationale behind the language model's outputs. In principle, the langua

researcharxiv-cs-cl

16 Oct 2026

CarryOn: A Dual-Loop Harness for Personalized and Reliable Robot Assistance

arXiv:2610.21453v1 Announce Type: cross Abstract: While generalist vision-language-action (VLA) models have enabled diverse open-world manipulation, real-world robotic assistance requires two critical

safetyarxiv-cs-cv

CAT-alyzing Honesty: Continuous Adversarial Training for Transferable LLM Honesty

arXiv:2610.22292v1 Announce Type: cross Abstract: Large language models (LLMs) are becoming prevalent in scenarios where honesty is critical. However, despite alignment training, these models still ex

Close Enough is Nowhere Near: Fidelity-Consumability Decoupling in KV Caches

arXiv:2610.22016v1 Announce Type: new Abstract: Multi-agent LLM systems communicate in text, which is lossy and wasteful: the sender throws away the reading it already did. A growing literature instea

agentsarxiv-cs-lg

Applications

CoCopula: Conformal Calibration and Copula Aggregation for Reliable Renewable Energy Forecasting

arXiv:2602.02583v2 Announce Type: replace Abstract: The rapid growth of renewable energy penetration has intensified the need for reliable probabilistic forecasts to support grid operations at aggrega

applicationsarxiv-cs-lg

congrats to the StepFun team on releasing Step 5 Preview open weights today we’re excited to be a launch partner and to support another Step…

model-releasestogether-ai--x

congrats to the StepFun team on releasing Step 5 Preview open weights today we’re excited to be a launch partner and to support another StepFun release as they bring Step 5 Preview to developers Step

Local Ai

DST-Net: Decomposed Spatio-Temporal Network for Time Series Forecasting

arXiv:2610.21123v1 Announce Type: cross Abstract: Series decomposition has emerged as a widely acknowledged paradigm in deep time series forecasting models. However, existing approaches predominantly

local-aiarxiv-cs-ai

DuET: Note-Frame Dual Encoding for Piano Performance-to-Score Transcription

arXiv:2610.21467v1 Announce Type: cross Abstract: Transcribing expressive piano performances into scores requires interpreting individual note timings within an underlying metrical structure. However,

researcharxiv-cs-lg

Evaluation Awareness Beyond English: Do LLMs Act Differently When Tested in Indic Languages?

arXiv:2610.22333v1 Announce Type: new Abstract: Large language models (LLMs) can often tell when they are being tested. This ability, known as evaluation awareness, can lead models to act more cautiou

Expanding Attention: A Taylor-Series Route to Linear-Time Transformers with a Fixed Number of Recurrent States

arXiv:2610.20637v1 Announce Type: new Abstract: We expand the exponential kernel of attention into a truncated Taylor series of n terms and factorize each term into a tensor-power inner product, which

researcharxiv-cs-lg

Failure Is the Mother of Success: Recovering Supervision with Grounding Hindsight

arXiv:2610.21018v1 Announce Type: new Abstract: When every rollout for a problem fails, GRPO receives neither a successful exemplar nor a nonzero group-relative advantage, so it learns nothing from ex

Flow-CLIP: Image-Conditioned Residual Scoring for CompositionalImage-Text Matching

model-releasesarxiv-cs-cv

arXiv:2610.21937v1 Announce Type: new Abstract: Vision--language pre-training has enabled substantial progress in image--text retrieval and zero-shot recognition by learning transferable cross-modal r

Fractional Rotation, Full Potential? Investigating Performance and Convergence of Partial RoPE

arXiv:2603.11611v2 Announce Type: replace-cross Abstract: Rotary Positional Embedding (RoPE) is widely used in transformers to encode relative positional information, yet the effect of applying RoPE t

researcharxiv-cs-cl

GeoState: Learning View-Decoupled Geometry States for 3D World Modeling

arXiv:2610.22343v1 Announce Type: cross Abstract: Recent 3D world models increasingly use features from geometry foundation models (GFMs) as predictive world states, benefiting from their rich geometr

GRADS: Graph-Regulated Agentic Data Synthesis with Controllable Difficulty

arXiv:2610.21167v1 Announce Type: new Abstract: Deep research agents are increasingly deployed to retrieve precise information from large corpora, yet multi-hop, long-horizon tasks remain challenging.

GraphACM: Graph-based Action Consistency Measurement for Uncertainty Quantification in LLM Agents

arXiv:2610.22031v1 Announce Type: new Abstract: Behavioral consistency across repeated executions provides an informative signal for assessing the reliability of large language model (LLM) agents. How

GraphBEAT: Graph-based Bucketized Event Aggregation Over Time for Early Risk Stratification of Gastrointestinal Cancers

arXiv:2610.22014v1 Announce Type: cross Abstract: Longitudinal electronic health records (EHRs) contain complementary diagnostic and laboratory information about patient health. However, irregularity,

researcharxiv-cs-ai

GSM: Efficient Language Modeling with Shared Global State

arXiv:2609.33465v3 Announce Type: replace Abstract: Improving language model efficiency requires not only cheaper operations but also eliminating redundant computation. We argue that effective modelin

Identifying Effective Strategies in Prompt Evolution for Stress and Emotion Prediction

arXiv:2610.21407v1 Announce Type: new Abstract: Early stress detection and risk prediction are crucial for timely mental health assessment and support. While large language models have recently shown

researcharxiv-cs-cl

Applications

IDfRA: Self-Verification for Iterative Design in Robotic Assembly

arXiv:2509.16998v2 Announce Type: replace Abstract: Design for Robotic Assembly (DfRA) remains largely dependent on manual planning and heuristic simulation, limiting scalability and robustness in com

applicationsarxiv-cs-ro

It really just needs some encouragement (Qwen3.8-27B-UD-IQ4_XS)

model-releasesr-localllama

I know I am probably missing the point of this benchmark, but I wanted to see if the model is capable of generating something better or is that the best it can do. So I gave it some encouragement. I f

Jev-LiteMAS: Separating Decisions from Generation in Multi-Agent Workflows

arXiv:2610.21411v1 Announce Type: new Abstract: Multi-agent LLM systems rely on generative models for expert execution, workflow planning, and artifact review. Yet many coordination operations require

Kolab: Benchmarking Human-Agent Collaboration in Long-Horizon Workflows

model-releasesarxiv-cs-ai

arXiv:2610.21109v1 Announce Type: new Abstract: When humans collaborate with AI agents on long-horizon tasks, what happens to the agents' contributions? For solving long-horizon tasks, humans place gr

Local Ai

L2GSSL: Label-Efficient Local-to-Global Self-Supervised Learning for Volumetric Healthcare Data

arXiv:2610.21356v1 Announce Type: new Abstract: Healthcare institutions routinely accumulate high-dimensional computed tomography (CT) volumes, but only a fraction can be annotated by experts. We pres

local-aiarxiv-cs-cv

Large Language Models Naively Recover Ethnicity from Individual Records

arXiv:2601.21132v2 Announce Type: replace Abstract: I demonstrate that large language models can infer ethnicity from names with accuracy exceeding that of Bayesian Improved Surname Geocoding (BISG) w

LCT: Losslessly Compressed Tensors with GPU friendly execution for Training

model-releasesarxiv-cs-lg

arXiv:2610.22179v1 Announce Type: new Abstract: Lossless tensor compression could reduce memory usage during training, but training requires tensors to be repeatedly re-encoded. We introduce Losslessl

Tutorials

Learn Only Where You Can't Compute: Structured Corrections to Gaussian Process Posteriors

arXiv:2610.21977v1 Announce Type: new Abstract: Physics-informed Gaussian processes (GPs) provide a principled framework for scientific inference by expressing uncertainty over empirical measurements,

tutorialsarxiv-cs-lg

Learning to Steer LLM Agents and Multi-Agent Systems

arXiv:2610.22316v1 Announce Type: cross Abstract: Large language model (LLM)-based agents and multi-agent systems increasingly tackle complex tasks through long-horizon tool use and inter-agent collab

Lexical Reference Frames: Interpreting LM Residual Streams in Native Semantics

arXiv:2610.22169v1 Announce Type: new Abstract: The vocabulary of a language model is its native semantics: the embedding and the unembedding fix the meaning of a state at the two ends of the residual

researcharxiv-cs-cl

Loud and Clear: Making Visual Evidence Count in Multimodal Document RAG

arXiv:2610.21318v1 Announce Type: cross Abstract: Multimodal document retrieval-augmented generation (RAG) has focused largely on retrieval, yet its answers depend on how well a vision-language model

researcharxiv-cs-ai

MemComposer: Learning to Assemble Memories for LLM Agents via Reinforcement Learning

arXiv:2610.21091v1 Announce Type: new Abstract: Agent memory enables large language model (LLM) agents to reuse past experiences without updating their parameters. However, semantic similarity alone d

Mind the Tail: Data Selection Through Sparse Concepts

arXiv:2610.21007v1 Announce Type: new Abstract: Data selection reallocates training support across visual concepts, including objects, attributes, color, texture, and backgrounds. Different allocation

researcharxiv-cs-cv

model : MTP support for Mellum2.1 by Xarbirus · Pull Request #30612 · ggml-org/llama.cpp

model-releasesr-localllama

Mellum2.1 Highlights Mellum2.1 is the next version of Mellum2 Thinking. The architecture is unchanged (a 12B mixture-of-experts model with 2.5B active parameters), and almost all of the work for this

Momentum, Commentary Tone, and Earnings Surprise in LLM Financial Forecasts

model-releasesarxiv-cs-ai

arXiv:2610.22043v1 Announce Type: cross Abstract: Which inputs drive a language model's financial forecast? We construct synthetic earnings announcements that independently reverse 20-day momentum, no

Tutorials

Multi-sourced AI Tutor for Non-Native English Speaker Students

arXiv:2610.22163v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being adopted as teaching tools in computing education, particularly for developing AI tutors capable of a

tutorialsarxiv-cs-ai

Tutorials

Multi-Target Few-Shot Prompting with Diffusion Language Models

arXiv:2610.22294v1 Announce Type: new Abstract: Few-shot prompting is useful when instructions and rewards are hard to specify. One such application is editing by example, where a demonstrated formatt

tutorialsarxiv-cs-cl

Multimodal AI Detection for Math-Heavy Scientific Text

arXiv:2610.21062v1 Announce Type: new Abstract: As large language models become increasingly capable of generating, and assisting with, scientific writing, there is a need for greater transparency and

Muse Spark Open is now live on Wally, day 0 Best US open model thanks to @finkd 370 tok/s, ~2x faster than any provider on OpenRouter. $5 Fr…

Muse Spark Open is now live on Wally, day 0 Best US open model thanks to @finkd 370 tok/s, ~2x faster than any provider on OpenRouter. $5 Free on signup. Media 1/ muse spark open is the most capable U

agentsyohei-nakajima--x

MuSTMM: Learning Sound-Triggered Mobile Manipulation across Multiple Scenes

model-releasesarxiv-cs-ro

arXiv:2610.21429v1 Announce Type: new Abstract: Sound-Triggered Mobile Manipulation (STMM) requires robots to respond to sound events by navigating to the associated objects and performing appropriate

NeoHorse-1: Towards Recursive Self-Improvement via Agentic Post-Training with Routing Harness

arXiv:2609.08183v2 Announce Type: replace Abstract: Recursive self-improvement (RSI) requires a concrete mechanism through which an AI system observes its capabilities and converts that evidence into

safetyarxiv-cs-cl

Onboard Lightweight LLM Reasoning for Human-Aware Safe UAV Navigation

model-releasesarxiv-cs-ro

arXiv:2610.22092v1 Announce Type: new Abstract: Aerial robots operating near people must treat a pedestrian, a parked car, and a wall differently, yet conventional perception--planning stacks reduce a

One Is Not Enough: How People Use Multiple AI Models in Everyday Life

arXiv:2603.26107v1 Announce Type: cross Abstract: People increasingly use multiple Multimodal Large Language Models (MLLMs) concurrently, selecting each based on its perceived strengths. This cross-pl

OpCredit: Operation-Aware Policy Learning for Agentic Knowledge Graph Question Answering

arXiv:2610.21345v1 Announce Type: new Abstract: Agentic knowledge graph question answering(KGQA) relies on sequences of executable operations, but trajectory-level rewards obscure their individual con

safetyarxiv-cs-cl

Open-world AI: a Tale of Three Requirements

arXiv:2610.20782v1 Announce Type: new Abstract: The closed world asks AI for specialized competence and lets it manufacture the iid data its theory assumes: a fixed criterion licenses collecting examp

researcharxiv-cs-ai

OPRD: On-Policy Reminder Distillation for Long-Horizon Coding Agents

arXiv:2610.21496v1 Announce Type: new Abstract: Reliable repository-level coding requires agents not only to generate correct code but also to preserve constraints and respond to tool feedback across

Perceive, Predict, and Plan: a Unified World Action Model for Egocentric Dexterous Manipulation

arXiv:2610.22363v1 Announce Type: new Abstract: We introduce P^{3}-WAM, a unified world action model for egocentric dexterous manipulation that learns 3D perception, action-conditioned prediction, and

researcharxiv-cs-cv

Pixels to Tokens: Token Space Efficient Active Learning for Low-Budget Semantic Segmentation

arXiv:2610.20881v1 Announce Type: new Abstract: While foundation models and vision transformers (ViTs) have redefined visual representations, current active learning (AL) strategies for these backbone

researcharxiv-cs-cv