Search: “models”

Continual Learning for Reliable In-Sequence Molecular Communication

arXiv:2610.20426v1 Announce Type: new Abstract: This paper considers reliable in-sequence molecular communication, where bio-nanomachines exchange molecule-encoded information in a specified order, an

researcharxiv-cs-lg

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Coordi-pi: Coordination-Aware Dual-Hand Action Representation for Bimanual Dexterous Manipulation

DGX agent

arXiv:2610.19753v1 Announce Type: new Abstract: Vision-language-action (VLA) models have shown strong potential for general-purpose robotic manipulation, but extending them to bimanual dexterous manip

applicationsarxiv-cs-ro

15 Oct 2026

Counterfactual Regret for Reflective Agents with Lean-Verified Guarantees

arXiv:2610.14790v1 Announce Type: new Abstract: Reflective language agents reuse feedback and memory to adapt across tasks without updating model weights. However, existing guarantees for policy selec

safetyarxiv-cs-ai

Tools

Dialectic 60: Patrick Hsu! @pdhsu & @arcinstitute are combining biology, engineering, and AI to turn a sci-fi future into reality. Patrick g…

Dialectic 60: Patrick Hsu! @pdhsu & @arcinstitute are combining biology, engineering, and AI to turn a sci-fi future into reality. Patrick got expelled from college at 13, returned at 15, later worked

toolslinus-lee--x

Did the LLM Answer the Question? A Semantic Reconstruction Game for Jailbreak Evaluation

arXiv:2610.19306v1 Announce Type: new Abstract: Jailbreak attacks against large language models (LLMs) are evaluated using attack success rate (ASR), which depends on correctly identifying responses t

Tutorials

Do LLM Tutors Actually Teach? A Process-Centered Synthesis of the Tutoring Loop

arXiv:2610.15692v2 Announce Type: replace Abstract: Large language models can produce fluent tu- toring dialogue, but whether they actually help students learn remains unclear. We present a process-ce

tutorialsarxiv-cs-cl

Dynamic Conflict Clustering with Lightweight Learning and Strategic Repair for Distributed Constraint Satisfaction

arXiv:2610.15658v1 Announce Type: cross Abstract: Distributed Constraint Satisfaction Problems (DCSPs) model distributed decision-making in multi-agent systems, where agents assign values to local var

ECMR: Evidence-Aware Deliberation Control for Multi-Agent LLM Reasoning

arXiv:2610.17869v1 Announce Type: new Abstract: Multi-agent Large Language Model (LLM) systems typically commit to a deliberation protocol before inference. A fixed protocol cannot allocate computatio

Equal CER, Unequal Damage: Severity-Weighted Character Error Rate for OCR

arXiv:2610.20461v1 Announce Type: new Abstract: Character Error Rate (CER), the standard metric for OCR and vision-language models (VLMs), charges a typo as much as a wrong name. We introduce semCER,

safetyarxiv-cs-cl

Equal-information evaluation of credit assignment in modular financial reinforcement learning

arXiv:2610.14750v1 Announce Type: new Abstract: Credit assignment in modular financial reinforcement learning is difficult to evaluate because an attributed signal may improve a component loss without

EvoQuantLab: Training-Free Dual-Loop Evolution for Auditable Quantitative Research

arXiv:2610.17130v2 Announce Type: new Abstract: Automated alpha factor discovery is critical for modern quantitative research. While large language models (LLMs) have increasingly been integrated into

FoveaVLA: Foveation Actions Replace the Wrist Camera in VLAs

arXiv:2610.20064v1 Announce Type: new Abstract: We present FoveaVLA, a Vision-Language-Action (VLA) model that replaces the wrist camera with learned foveation actions. Wrist cameras provide close-up

safetyarxiv-cs-ro

From Chasing Ghosts to Missed Attacks: Perspectives and Perceptions of SOC Practitioners on LLM Integration, Risks, and Readiness

arXiv:2608.00672v2 Announce Type: replace-cross Abstract: Security Operations Centers (SOCs) process large volumes of security events, requiring analysts to accurately detect and assess ongoing cybera

applicationsarxiv-cs-ai

Hindsight-Privileged RLVR: Single-Rollout Token Credit Without Group Sampling

arXiv:2610.20497v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) trains language models from checked task outcomes, but assigning a terminal reward to individual r

Horizon Scans can be accelerated using novel information retrieval and artificial intelligence tools

arXiv:2504.01627v2 Announce Type: replace-cross Abstract: Introduction: Horizon scanning in healthcare assesses early signals of innovation, crucial for timely adoption. Current horizon scanning faces

applicationsarxiv-cs-ai

HyrCap: Hybrid Rank-Calibration of Action Proposals for Temporal Event Understanding

arXiv:2610.19526v1 Announce Type: new Abstract: Temporal action detection in long untrimmed videos suffers from inaccurate localization and low-quality proposals, especially with sparse annotations an

local-aiarxiv-cs-cv

Instruction Mining From Images: Constructing a Synthetic Dataset for Multimodal Learning ILSP DCVLR Competition Submission

arXiv:2610.19932v1 Announce Type: new Abstract: This work presents a compact and reproducible pipeline for synthesizing and curating image-based instruction-response pairs for DCVLR. We draw from the

researcharxiv-cs-cv

Interpolation of GEDI Biomass Estimates with Calibrated Uncertainty Quantification

arXiv:2601.16834v4 Announce Type: replace-cross Abstract: Wall-to-wall biomass density estimation from NASA's GEDI mission requires interpolating sparse LIDAR observations across heterogeneous landsca

local-aiarxiv-cs-cv

Keep Your Receipts: Trustworthy Cleanup of Agent-Built Knowledge Graphs

arXiv:2610.17719v1 Announce Type: new Abstract: Agents build knowledge graphs as memory, and building them has become easy. Maintaining them has not. When a source is retracted, overruled, or erased,

Label-Centric Knowledge Retrieval for Zero-Shot Text Classification

arXiv:2610.16182v1 Announce Type: new Abstract: Flagship large language models (LLMs) offer rich general knowledge and strong reasoning capabilities, but their high inference cost and latency limit th

applicationsarxiv-cs-ai

Tutorials

lambda_0: Scaling Open-World Egocentric Human Data for Humanoid Loco-Manipulation

arXiv:2610.18950v1 Announce Type: cross Abstract: Humanoid loco-manipulation requires coordinated whole-body interaction with the physical world, yet collecting robot demonstrations at scale remains c

tutorialsarxiv-cs-cv

Learning Proposition-Level Links from Sentence-Level Supervision for Neuro-Symbolic NLI

arXiv:2610.15158v2 Announce Type: replace Abstract: We study neuro-symbolic natural language inference (NLI) with independently translated propositional representations of the premise and hypothesis.

researcharxiv-cs-cl

Limitations on Autoregressive Token Generation via Sequential Sampling

arXiv:2610.14615v1 Announce Type: cross Abstract: We study autoregressive token generation through the notion of sequential samplers: A circuit that samples the next symbol only given the previous one

safetyarxiv-cs-ai

Tutorials

LLMs program using Reusable and Composable Abstract Representations

arXiv:2610.19238v1 Announce Type: new Abstract: When writing code, the same computation can be expressed in different programming languages and through different implementation strategies. We show tha

tutorialsarxiv-cs-lg

Logarithmic Scores, Power-Law Discoveries: Disentangling Measurement from Coverage in Agent-Based Evaluation

arXiv:2604.00477v2 Announce Type: replace Abstract: LLM-based agent judges are an emerging approach to evaluating conversational AI, yet a fundamental uncertainty remains: can we trust their assessmen

LYNX: Analytical Program Synthesis via Grounding and Closed-Loop Refinement

arXiv:2610.14777v1 Announce Type: new Abstract: LLM-powered data analytics aims to translate natural language instructions into executable analytical programs over underlying data. However, existing a

MCAIR: Monitoring and Correcting Agent Unfaithfulness via Internal Representations

arXiv:2610.19679v1 Announce Type: cross Abstract: Large Language Model (LLM)-based agents have demonstrated remarkable capabilities in completing complex tasks through multi-step reasoning and tool in

agentsarxiv-cs-lg

MemDuet: Learning Dual-Process Memory for Long-Context Reasoning

arXiv:2610.19928v1 Announce Type: new Abstract: Reasoning over infinitely long documents is becoming a reality with recurrent memory agents. However, increasing context length exacerbates the trade-of

safetyarxiv-cs-cl

Mitigating Cross-Modal Hallucinations by Correcting Modality Misrouting in Omnimodal LLMs

arXiv:2610.18141v1 Announce Type: new Abstract: Omnimodal large language models (OLLMs) are susceptible to cross-modal hallucinations under audio-visual interference. We find that, for a substantial f

MMLA-RSI: Recursive Self-Improvement through RTT and RTMA

arXiv:2610.20294v1 Announce Type: new Abstract: An agent can improve its behavior within an unresolved problem by changing how it acts and which experience it retains. We propose MMLA-RSI, a recursive

safetyarxiv-cs-cl

MUCO: A Mani-Unit-Structured Manipulation Framework for Compositional Long-Horizon Robot Tasks

arXiv:2610.19913v1 Announce Type: new Abstract: Learning and executing long-horizon robot manipulation as complete task trajectories raises data-collection costs, lim?its capability reuse, and causes

local-aiarxiv-cs-ro

Multi-Horizon Explainable Queue Forecasting and Resource-Aware Decision Support for Intelligent Border Control Using LightGBM

arXiv:2610.15930v1 Announce Type: new Abstract: Border crossing points are stochastic service systems in which traffic demand, traveler categories, registration status, inspection requirements, staffi

Muse Spark Open is now live on Together AI. We're proud to be a Day 0 launch partner for @AIatMeta's Muse Spark Open, the most capable US op…

Muse Spark Open is now live on Together AI. We're proud to be a Day 0 launch partner for @AIatMeta's Muse Spark Open, the most capable US open-weights model to date, built for long-running agentic cod

agentstogether-ai--x

Hardware

NVIDIA Expands Advanced Technology Access for Europe’s Scientific Community Through Open Learning Resources, Collaborations and Compute

Much of today’s scientific progress begins with computation. But turning accelerated computing’s potential into scientific progress — modeling climate systems, designing molecules, simulating material

hardwarenvidia-blog

ollama run lfm2.5:24b https://ollama.com/library/lfm2.5:24b

ollama run lfm2.5:24b https://ollama.com/library/lfm2.5:24b Today we release 𝙻𝙵𝙼𝟸.𝟻-𝟸𝟺𝙱-𝙰𝟸𝙱, the largest 𝙻𝙵𝙼𝟸.𝟻 family member. It is an efficient local model for laptops and PCs to work through multi-

local-aiollama--x

Online Tokenization with Optimal Delay in Linear Time

arXiv:2610.19139v1 Announce Type: cross Abstract: Tokenization is an essential preprocessing step in almost all large language models (LLMs). One of the most popular frameworks is BPE tokenization, wh

researcharxiv-cs-lg

PANINI-DR: Controlled Deep Research through Generative Semantic Workspaces

arXiv:2610.15208v1 Announce Type: cross Abstract: Deep research requires connecting multiple steps of search, reasoning, and computation, with intermediate findings guiding what to investigate next. A

Player-1: Learning to Play from Synthetic Experience

arXiv:2610.20584v1 Announce Type: new Abstract: Computer-use agents have demonstrated strong capabilities in interpreting screens and executing keyboard and mouse actions. However, games, with their v

agentsarxiv-cs-cv

Post-Training, Finetuning, and Steering:A Field Guide for Curating Training Data

arXiv:2610.19143v1 Announce Type: new Abstract: While Vision-Language-Action models have enabled impressive cross-task transfer in zero-shot settings, adaptation methods are often necessary to achieve

safetyarxiv-cs-ro

Queue-Aware Token Communications: Bridging AI Representation and Wireless Service

arXiv:2610.16730v1 Announce Type: new Abstract: The rapid advancement of foundation models and edge intelligence is transforming wireless networks from data-oriented communication systems into artific

Rational Transductors

arXiv:2602.07599v2 Announce Type: replace Abstract: Standard Transformers excel at semantic modeling but struggle with rigid sequential logic and state tracking. Theoretical work establishes that self

researcharxiv-cs-lg

RCR-Router: Efficient Role-Aware Context Routing for Multi-Agent LLM Systems with Structured Memory

arXiv:2508.04903v4 Announce Type: replace-cross Abstract: Large language model (LLM) agents are increasingly organized into multi-agent systems for complex reasoning and decision-making tasks. However

REA: From Correct LLM Judgments to Safe Decision Delivery

arXiv:2610.17473v1 Announce Type: new Abstract: Generative safety guards must classify requests correctly and return outputs that applications can parse. Reasoning guards can improve classification ac

safetyarxiv-cs-ai

ReAl: Refine neural operators via aligning dynamical flow

arXiv:2610.20369v1 Announce Type: new Abstract: Neural partial differential equation (PDE) surrogates trained with mean squared error (MSE) can capture dominant dynamics but often lose high-frequency

Recovering Reliable Supervision via Critique-Guided On-Policy Distillation

arXiv:2610.20572v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student model on its own rollouts with token-level supervision from a teacher, assuming that the teacher can reach

ReCreate: Reasoning and Creating Domain Agents Driven by Experience

arXiv:2601.11100v3 Announce Type: replace Abstract: Large Language Model (LLM) agents are reshaping the industrial landscape. However, most practical agents still rely on human-designed scaffolds, mak

Resolution Allocation with Learnable Resizing and Spectral Filter Parameterization

arXiv:2610.20274v1 Announce Type: cross Abstract: Learnable downsampling and spectral-domain filter parameterizations have each made convolutional networks more flexible, but their interaction has not

researcharxiv-cs-cv

Retrieve What Helps, Only When It Helps: Agentic Reinforcement Learning for Selective Retrieval-Augmented Machine Translation

arXiv:2610.19528v1 Announce Type: new Abstract: Retrieving external knowledge can improve large language model (LLM) translation by providing supplementary information such as idiom interpretations an

agentsarxiv-cs-cl