Search: “reasoning”

gwBenchmarks: Stress-Testing LLM Agents on High-Precision Gravitational Wave Astronomy

model-releasesarxiv-cs-ai

arXiv:2605.11269v2 Announce Type: replace-cross Abstract: Modern gravitational wave astronomy relies on modeling tasks that often require months of graduate-level effort, including building fast wavef

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Agents

Hierarchical Floorplan-Guided Vision-Language Exploration for Embodied Question Answering

DGX agent

arXiv:2609.26360v1 Announce Type: new Abstract: Embodied Question Answering (EQA) requires an agent to explore a previously unseen environment, gather relevant information, and answer questions about

agentsarxiv-cs-ro

23 Sept 2026

Impact Is Not Invalidation: Ask About the Claim, Not the Diff

arXiv:2609.25130v1 Announce Type: new Abstract: Memory systems for coding agents must decide, when a repository changes, which of their stored claims have become false. Content anchoring invalidates a

researcharxiv-cs-cl

Interpretable AI plus Handheld, Portable Retinal Photographs: A Low-Cost Glaucoma Screening Solution for West Africa

arXiv:2609.25697v1 Announce Type: new Abstract: Purpose: To develop and evaluate an interpretable artificial intelligence (AI) framework for glaucoma screening from low-cost portable, handheld retinal

researcharxiv-cs-cv

⚡ Meet Qwen-Audio-3.1! ASR, TTS & Realtime are fully upgraded, joined by two new models: TTS-Next for audio creation and ASR-Next for audio …

⚡ Meet Qwen-Audio-3.1! ASR, TTS & Realtime are fully upgraded, joined by two new models: TTS-Next for audio creation and ASR-Next for audio understanding. Five models, one complete audio stack: unders

model-releasesqwen--x

Mitigating LLM Over-Refusal via Dynamic Semantic Routing Calibratione

arXiv:2609.25049v1 Announce Type: new Abstract: Large language models (LLMs) aligned for safety often suffer from over-refusal, incorrectly rejecting benign yet safety-related instructions. Prior stud

local-aiarxiv-cs-cl

MotionForge: A Data Generation Pipeline and Large-Scale Benchmark for Long-Horizon Manipulation of Dynamic Objects with Domain Shifts

arXiv:2609.25689v1 Announce Type: new Abstract: Recent advances in learning-based robot policies have demonstrated promising progress, yet they are predom- inantly evaluated in static or quasi-static

OpenQlaw: An Agentic AI Assistant for Analysis of 2D Quantum Materials

arXiv:2603.17043v2 Announce Type: replace Abstract: Physics-aware multimodal large language models (MLLMs) can localize and characterize two-dimensional (2D) material flakes from optical microscopy im

local-aiarxiv-cs-cv

Optimizing Denoising Trajectories in dLLMs: A Lightweight Evolutionary Heuristic Approach

arXiv:2609.26052v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have recently emerged as a promising alternative to conventional Auto-Regressive (AR) Large Language Models (LLM

PAANI : On Device Visual Evidence Fusion and Explainable Guidance for River Robot Simulation

arXiv:2609.22353v1 Announce Type: new Abstract: Mobile river monitoring robots must interpret obstacles and water boundaries that geographic waypoints alone cannot describe. On resource constrained pl

local-aiarxiv-cs-ai

PACE-dLLM: Elastic Block Decoding via Confidence Cliff Estimation for Diffusion Language Models

arXiv:2609.26249v1 Announce Type: new Abstract: Diffusion language models (dLLMs), such as LLaDA and Dream, have become competitive with autoregressive (AR) LLMs in generation quality while supporting

researcharxiv-cs-cl

PACT: From Credit Assignment to Critic Alignment

arXiv:2609.26355v1 Announce Type: new Abstract: Reinforcement learning has become a central component of large language model (LLM) post-training, yet token-level credit lacks a generally accepted mat

safetyarxiv-cs-lg

PermuFormer: Multi-Task Pretraining for Permutation Representation in Algebraic Combinatorics

arXiv:2609.25438v1 Announce Type: new Abstract: Diverse pretraining has been shown to be an effective method for learning reusable, domain-aware representations that provide a starting point for fine-

researcharxiv-cs-lg

Prompt Breadth and Rollout Refresh Interact in On-Policy Distillation

arXiv:2609.25048v1 Announce Type: new Abstract: How many prompts does on-policy distillation (OPD) need, and how does the answer depend on the student policies that generate its training responses? We

safetyarxiv-cs-cl

QwenImage 2.1 vs QwenImageEdit 2511 (2.1 is not better for every task)

model-releasesr-stablediffusion

First: That the 7GB (int8) 2.1 comes even close to the 20GB (int8) 2511 is amazing, but maybe because of the smaller size some capabilities got lost. For some tasks 2.1 it is much better than 2511, bu

SambaGraph: Action-Reaction Spatio-Temporal Graphs for Soccer Tactical Response Modeling

model-releasesarxiv-cs-lg

arXiv:2609.25569v1 Announce Type: new Abstract: Soccer tactics are interactive: an attacking action changes the opponent's defensive problem, and the observed response depends on the multi-agent match

Same Chart, Different Story: Bias in Vision-Language Chart Interpretation

arXiv:2609.26210v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly used to interpret charts and generate natural-language explanations for socially consequential data. Howe

Same Quantity, Different Answer: Numerical Representation Invariance in Language Models

arXiv:2609.25009v1 Announce Type: new Abstract: Numerically equivalent word problems should yield the same canonical answer whether a quantity is written as a decimal, fraction, percentage, number wor

Situation Aware Locomotion for Dual Mobile Cobots in Shared Environments

arXiv:2609.26083v1 Announce Type: new Abstract: This paper presents a situation aware locomotion framework for two mobile collaborative robots operating in shared industrial environments. The proposed

safetyarxiv-cs-ro

STRUCTUREDAGENT: Planning with AND/OR Trees for Long-Horizon Web Tasks

arXiv:2603.05294v3 Announce Type: replace Abstract: Existing LLM-based web agents struggle on complex, long-horizon tasks due to limited in-context memory, weak planning abilities, and greedy behavior

researcharxiv-cs-ai

SyzHarness: Patch-Based Kernel Bug Reproduction with LLM-Synthesized Fuzzing Harnesses

model-releasesarxiv-cs-ai

arXiv:2609.23889v1 Announce Type: cross Abstract: Automated kernel vulnerability reproduction is essential for bug triage, patch validation, and regression testing, but still lacks an effective and ef

Applications

Targeted Review for AI-Assisted Biodiversity Surveys: Active Continuous-Score Occupancy Modeling

arXiv:2609.25657v1 Announce Type: new Abstract: We increasingly use machine learning to label scientific datasets. The models we develop and deploy are improving all the time, but they are not and wil

applicationsarxiv-cs-lg

There’s an enormous amount of open training data on Hugging Face. What does it take to make it work together 🤗? For Marin’s 535B run, we bu…

model-releasesclem-delangue--x

There’s an enormous amount of open training data on Hugging Face. What does it take to make it work together 🤗? For Marin’s 535B run, we built on 25T tokens from 152 datasets with licenses permitting

What AI models can I realistically run on my GTX 1050 Ti laptop?

Hey everyone, I’m new to running AI models locally and I’d like some advice. My laptop specs are: HP OMEN 15 CPU: Intel i5-8300H RAM: 16 GB GPU: NVIDIA GTX 1050 Ti 4 GB VRAM OS: Windows I’m planning t

local-air-ollama

What local Ollama models would you recommend for my PC? (RTX 5060 Ti 16GB)

Hey everyone, I'm getting into running LLMs locally with Ollama and would like some recommendations on which models I should realistically run with my hardware. My PC specs GPU: RTX 5060 Ti 16GB VRAM

local-air-ollama

What Should a Self-Teacher See? Privileged Context Design for On-Policy Self-Distillation

arXiv:2609.25623v1 Announce Type: new Abstract: More privileged information does not always make a better teacher. We study this tension in on-policy self-distillation (OPSD), where a frozen copy of t

safetyarxiv-cs-lg

Which small model works best with Ollama on a Raspberry Pi 5?

I've been comparing and working on Gemma 4, Phi-4-Mini, and Qwen3-4B for local LLM use on an 8 GB Raspberry Pi 5. The results were indeed close, but each model has a different strength: Gemma 4 E2B: a

model-releasesr-ollama

You Only Need 2/3 of the Chosen Experts: An Empirical Study of Dynamic Expert Pruning in Fine-Grained MoE LLMs

arXiv:2609.25809v1 Announce Type: new Abstract: Fine-grained mixture-of-experts (MoE) architectures have become a mainstream design for open-weight LLMs, with hundreds of experts and increasingly many

researcharxiv-cs-lg

Applications

You Should Be Properly Scoring Your Odometry

arXiv:2609.25900v1 Announce Type: new Abstract: When we evaluate the performance of our odometry, it is common practice to score the estimated track against a ground truth. Unfortunately, scoring uses

applicationsarxiv-cs-ro

1% of Tokens Can Be Enough: On Gradient Estimation in On-Policy Distillation

arXiv:2609.24432v1 Announce Type: cross Abstract: Sparse on-policy distillation (OPD) allocates teacher supervision to a small subset of tokens in student-generated trajectories. However, useful teach

safetyarxiv-cs-cl

A Distributional Optimisation Perspective on Combining Models in Deep Learning

model-releasesarxiv-cs-lg

arXiv:2609.24328v1 Announce Type: new Abstract: Combining predictions from different models can improve performance at machine learning tasks, but the training of the individual models and the rule us

Applications

A Topological Representation with Object-Path Graphs for Open-Vocabulary Instance Navigation

arXiv:2609.24189v1 Announce Type: new Abstract: Vision-language navigation requires embodied agents to navigate environments using natural language instructions and visual observations. Existing appro

applicationsarxiv-cs-ro

Action-Slot: Structured Action-Centric Representation Learning for Multi-Agent Atomic Activity Understanding

arXiv:2609.24127v1 Announce Type: new Abstract: Atomic activity understanding aims to recognize and localize structured traffic behaviors that jointly encode motion patterns and their grounding in roa

safetyarxiv-cs-cv

ActiveArena: Benchmarking and Understanding Active Perception in Robotic Manipulation

arXiv:2609.24124v1 Announce Type: new Abstract: Active perception and manipulation are crucial for robots to interact with complex scenes. Existing benchmarks struggle to evaluate how robots effective

Hardware

AgentRouter: Heterogeneous Model Routing for Cost-Optimal Multi-Step Agentic Workflows

arXiv:2609.22951v1 Announce Type: cross Abstract: Enterprise agentic systems that route every trajectory step to a frontier model waste 60-80% of their inference budget on subtasks that smaller models

hardwarearxiv-cs-cl

Agents

AgentSTAR: Agentic Shape Tracking and Reconstruction from Monocular Videos

arXiv:2609.24487v1 Announce Type: new Abstract: In this work, we present a method for shape reconstruction and tracking from video via agentic analysis-by-synthesis. Unlike prior methods which first e

agentsarxiv-cs-cv

Anthropic's Claude Opus 5.5 is now available in Hermes Agent via Nous Portal!

model-releasesnous-research--x

Anthropic's Claude Opus 5.5 is now available in Hermes Agent via Nous Portal! OPUS 5.5 BENCHMARKS JUST DROPPED. It beats Fable 5.1 and GPT 6 Astra across the board. Agentic coding, knowledge work, rea

AR-WAM: A Visual-Conditioned Agent-Ready World Action Model for Robotic Manipulation

arXiv:2609.23578v1 Announce Type: new Abstract: As AI agents become increasingly capable, agent-driven robotic control is emerging as a compelling paradigm. However, prevailing vision-language-action

Agents

AutoGym: Blueprint-First Generation of Verifiable Agent Gyms

arXiv:2609.22592v1 Announce Type: cross Abstract: Training agents with reinforcement learning requires a gym, comprising a task, an executable environment in which the task can be attempted, and a ver

agentsarxiv-cs-lg

ChartJudgeBench: Evaluating LMM Judges for Chart-to-Code Generation

model-releasesarxiv-cs-cv

arXiv:2609.24210v1 Announce Type: new Abstract: Building strong chart-to-code systems increasingly relies on reinforcement learning, whose effectiveness depends critically on the quality of the reward

Chronologic: Measuring Language Models' Ability to Represent the Past

arXiv:2609.23178v1 Announce Type: new Abstract: Language models are appealing tools for research on the past. But to trust the evidence a model provides, researchers need to know whether its responses

Commonsense-Grounded Path Planning from Abstract Instructions

arXiv:2609.22813v1 Announce Type: new Abstract: We present commonsense ranked search (CoRS), a novel path planner that turns an abstract instruction into a route that follows commonsense. While existi

Complex-valued Phase-Coherent Transformers

arXiv:2609.22415v1 Announce Type: new Abstract: Complex-valued Transformers have inherited softmax attention over the raw complex inner product. Outside natively complex domains this standard form sta

researcharxiv-cs-lg

Context Poisoning as Extreme-Value Attention Interference in Long-Context Language Models

arXiv:2609.22101v1 Announce Type: new Abstract: Large language models can process increasingly long prompts, yet their ability to locate and use decisive evidence may degrade as irrelevant or confusab

researcharxiv-cs-cl

D-JEPA: A Decision-Aligned Latent World Model

arXiv:2609.24749v1 Announce Type: cross Abstract: Latent world models predict the consequences of actions, but accurate prediction does not guarantee that latent distance reflects which candidate will

local-aiarxiv-cs-lg

Dial: A Knowledge-Grounded Dialect-Specific NL2SQL System

arXiv:2603.07449v2 Announce Type: replace-cross Abstract: Enterprises commonly deploy heterogeneous database systems, each of which owns a distinct SQL dialect with different syntax rules, built-in fu

Discrete Tokenization for Multimodal LLMs: A Comprehensive Survey

arXiv:2507.22920v2 Announce Type: replace Abstract: The rapid advancement of large language models (LLMs) has intensified the need for effective mechanisms to transform continuous multimodal data into

safetyarxiv-cs-cl

Do LLMs Choose Like Humans? Using Cognitive Theory to Evaluate LLM Decision-Making

arXiv:2609.22225v1 Announce Type: new Abstract: Large language models (LLMs) exhibit a range of human-like decision-making behaviors, but whether these reflect similar underlying mechanisms or surface