Search: “reasoning”

Test-Time Adaptation via Dual Distillation for Videos Under Severe Distribution Shifts

arXiv:2607.24611v1 Announce Type: new Abstract: Deep learning models have achieved state-of-the-art performance in several computer vision tasks. However, they experience severe performance degradatio

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The Physics of Multi-Turn Long-Horizon Planning: From Pre-training to Post-training via Single- and Multi-Teacher On-Policy Agentic Distillation

DGX agent

arXiv:2607.24720v1 Announce Type: cross Abstract: Multi-turn long-horizon planning is critical for foundation model agents, yet how to fundamentally improve it remains unclear. Existing models are tra

safetyarxiv-cs-ai

28 Jul 2026

The Scaffold Effect in Coding Agents: Harness Choice as a Hidden Variable in Coding-Agent Evaluation

model-releasesarxiv-cs-ai

arXiv:2607.22585v1 Announce Type: new Abstract: Public leaderboards for coding agents typically rank systems by model name and pass rate, while the surrounding harness (the scaffold that issues tools,

ThinkingCap-Qwen3.6-27B warrants a look

It has only been two days since I move 100% from Qwen3.5-27B F16 to ThinkingCap-Qwen3.6-27B F16. Where I was getting tps in 30-40 range (depending on the size of the context), I am definitely getting

Understanding Tone-Dependent Inference Cost in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2607.23915v1 Announce Type: cross Abstract: We examine how prompt tone affects both accuracy of the LLM answers and inference cost as reflected in output-token consumption. Experiments were perf

VecTree-RAG: An Agentic Retrieval-Augmented Generation Framework Combining Vector and Tree Retrieval for Efficiency and Accuracy

arXiv:2607.23006v1 Announce Type: cross Abstract: Scientific question answering requires a retrieval system to solve two distinct problems: identifying which papers are relevant and locating the suppo

local-aiarxiv-cs-ai

What Can I Edit? Open-Ended Strategy Discovery and the Emotion Editability Landscape

arXiv:2607.23920v1 Announce Type: new Abstract: Emotional image editing requires more than applying affective filters or modifying predefined visual factors: an effective edit must identify what a par

agentsarxiv-cs-cv

Why Anthropic's battle is meant to poison the wells of open weight models, in 3 steps.

It doesn't solve any problems. Just a few paragraphs above, he says he fears that authoritarian states (he names China, and possibly others) can use their models to do evil stuff. And surely enough, m

safetyr-localllama

Bowel Obstruction Detection and Localization on Abdominal CT with Deep Learning

arXiv:2607.22173v1 Announce Type: new Abstract: Bowel obstruction is a common and potentially life-threatening gastrointestinal condition. In the face of rising diagnostic workloads, the automated dia

local-aiarxiv-cs-cv

CARE: Anti-entanglement Ultrasound Image Segmentation via Channel-Aware Region Extrication

arXiv:2508.13899v2 Announce Type: replace Abstract: Accurate ultrasound image segmentation is fundamentally challenged by target-context entanglement, where lesion cues are easily mixed with surroundi

researcharxiv-cs-cv

CommandLM: Data driven behavior level descriptor for ego vehicles

arXiv:2607.22078v1 Announce Type: new Abstract: As autonomous driving systems move toward real-world deployment, interpretable, behavior-level decision-making is essential for safety, trust, and regul

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Dynamic Commonsense Coordination for Empathetic Response Generation

arXiv:2607.22136v1 Announce Type: new Abstract: Empathetic Response Generation (ERG) requires models to recognize users' emotions and generate empathetic responses. Commonsense knowledge has been show

Encoding Invisible Causation for Bridge Diagnostic Agents: Triple-Guided Retrieval-Augmented Fine-Tuning with QLoRA

model-releasesarxiv-cs-lg

arXiv:2607.21680v1 Announce Type: new Abstract: Bridge infrastructure deteriorates gradually, yet its root causes---salt intrusion, freezing, fatigue cracking, and others---remain invisible to the nak

Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs

arXiv:2607.22039v1 Announce Type: new Abstract: Model merging plays a crucial role in consolidating multiple specialized models into a single, unified model, especially in the era of large language mo

Evaluation design conditions the expert-vs-auto MeSH gap: a controlled comparison of bag-of-words and BiomedBERT on the Cohen benchmark

arXiv:2607.21685v1 Announce Type: new Abstract: A systematic review begins with someone reading thousands of abstracts to identify the few that are relevant, and classifiers are used to prioritise tha

EVL-MCoT: Enhanced Vision-Language Multi-CoT for Harmful Meme Detection

arXiv:2607.22016v1 Announce Type: new Abstract: MEMEs are widely used on the internet and often carry strong elements of sarcasm or irony. Understanding their hidden meanings typically requires a join

Happy to have @FireworksAI_HQ as our day0 launch partner and bring Kimi K3 to more developers. With Fireworks, you can now deploy and fine-t…

model-releaseskimi-moonshot--x

Happy to have @FireworksAI_HQ as our day0 launch partner and bring Kimi K3 to more developers. With Fireworks, you can now deploy and fine-tune the 2.8T Kimi K3 model with just a few clicks! Kimi K3 i

How much usage does Ollama Pro give right now vs direct API?

I'm considering the 20 Pro plan, but the limits seem to change over time and are hard to compare with direct API pricing. For anyone using Pro currently, roughly how much coding agent usage do you get

local-air-ollama

I ran the 35B agentic comparison someone asked for (stock vs Ornith vs KAT-Coder, 120 runs)

Someone in the comments of my 27B post-train bakeoff asked for the 35B version, so I ran it. Same setup as last time: fresh Coder workspaces on my k8s cluster, each driving my own agent (Hermes) headl

I want to run Kimi K3 at home, so I’m trying to make 2.8T-scale experimentation cheaper

Hey r/LocalLLaMA, I’m a retired engineer with a background in distributed computing, currently running a 1-person startup. Like many people here, I’d love to experiment with 2T+ MoE models locally. Th

local-air-localllama

IFCLoRA: Topology-Aware Rank Allocation for Parameter-Efficient Fine-Tuning

model-releasesarxiv-cs-lg

arXiv:2607.22251v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) is a widely used parameter-efficient fine-tuning method for large language models, but its performance depends strongly on ho

InteractComp: Evaluating Search Agents With Ambiguous Queries

arXiv:2510.24668v2 Announce Type: replace Abstract: Language agents have demonstrated remarkable potential in web search and information retrieval. However, many search-agent benchmarks assume that us

Interior interpretability with attention rollout: contraction and propagation profiles in Transformers

arXiv:2607.22367v1 Announce Type: new Abstract: Feature-attribution methods assign scores relating input variables to a model's output, but do not by themselves characterize how explicitly defined int

researcharxiv-cs-lg

Kimi K3 is live on Fireworks. Day 0, inference and training. US-hosted, and zero data retention. This is the first frontier open model in th…

model-releasesfireworks-ai--x

Kimi K3 is live on Fireworks. Day 0, inference and training. US-hosted, and zero data retention. This is the first frontier open model in the 3 trillion parameter class. It sports 1M context, native v

Kimi K3 is now available for inference & training in @FireworksAI_HQ. Crazy how easy they make it to tune frontier open models like K3 using…

Kimi K3 is now available for inference & training in @FireworksAI_HQ. Crazy how easy they make it to tune frontier open models like K3 using LoRA adapters. Best time to figure out how to own your inte

model-releasesdair-ai--x

LMEB: Long-horizon Memory Embedding Benchmark

arXiv:2603.12572v5 Announce Type: replace Abstract: Memory embeddings are crucial for memory-augmented systems, such as OpenClaw, but their evaluation is underexplored in current text embedding benchm

Looking forward to chatting with @hugobowne today (July 27) at 4 pm PT on the Vanishing Gradient livestream on YouTube. Will cover open sour…

agentssebastian-raschka--x

Looking forward to chatting with @hugobowne today (July 27) at 4 pm PT on the Vanishing Gradient livestream on YouTube. Will cover open source, the newest LLMs & trends, agent frameworks, and whatever

Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning

arXiv:2607.21653v1 Announce Type: cross Abstract: Agentic reinforcement learning research is constant algorithm modification, new estimators, new pipeline stages, new rollout schemes, and in mainstrea

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Moving Beyond Diversity: Visual Token Pruning as Subspace Reconstruction for Efficient VLMs

arXiv:2606.18681v2 Announce Type: replace Abstract: Despite their remarkable performance, Vision Language Models (VLMs) incur substantial computational overhead due to the large number of visual token

researcharxiv-cs-cv

Multi-Agent Debate and Visual Information Extraction for SeePhys Pro: A 1st-Place Technical Report from ICML 2026 AI4Math Track 3 Challenge

arXiv:2607.21946v1 Announce Type: new Abstract: This technical report presents our approach to Challenge Track~3: SeePhys Pro at the 3rd AI for Math Workshop, where the task is to answer college-level

agentsarxiv-cs-lg

New research from NVIDIA. They just dropped a PyTorch-native training framework for agentic RL. (bookmark it) Paper summary: Molt is a PyTor…

New research from NVIDIA. They just dropped a PyTorch-native training framework for agentic RL. (bookmark it) Paper summary: Molt is a PyTorch-native agentic RL framework with an unusual design target

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Nice little insights on doing autoresearch with coding agents. Hand a coding agent a dataset, an eval script, one editable file, and no supe…

Nice little insights on doing autoresearch with coding agents. Hand a coding agent a dataset, an eval script, one editable file, and no supervision. That's autoresearch and it tries to optimize the nu

model-releasesdair-ai--x

NVIDIA Nemotron 3 Ultra Leads Open Models on Accuracy and Efficiency in Agentic RTL Coding

model-releasesnvidia-developer

NVIDIA’s Nemotron 3 Ultra, when paired with the ACE‑RTL agent, achieves a 97.1 % average pass rate on the CVDP benchmark across nine RTL task categories—surpassing GLM 5.2 and Kimi K2.6 while using up

On Improving Faithfulness of Podcasts from Documents

arXiv:2607.21961v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to generate long-form conversational content such as podcasts from textual sources. While these syste

researcharxiv-cs-cl

Opaque Epistemic Mediation: How LLM Deployment Configurations Shape the Validation of Pseudo-Science

arXiv:2607.22513v1 Announce Type: cross Abstract: Commercial large language models are increasingly used as knowledge references, yet their stance on contested scientific claims is neither stable nor

Procedural Knowledge Is Not Low-Rank: Why LoRA Fails to Internalize Multi-Step Procedures

model-releasesarxiv-cs-lg

arXiv:2607.21612v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning methods like LoRA have become the default for adapting large language models, succeeding across instruction following,

Progress Reward Modeling for Robotic Learning: A Comprehensive Survey

arXiv:2607.21655v1 Announce Type: cross Abstract: Robotic learning takes place in dynamic environments with large behavior spaces. A terminal success signal only tells the robot whether the task is co

researcharxiv-cs-cl

Qwen3.6-27B speculative decoding gets better on heavier quants

I finished the speed leg of my spec-decode benchmarking for Qwen3.6-27B, main algorithms across quants. Overall: the heavier the quant, the more spec-decode buys you (10 of 10 speculative configs rank

Robot Learning to Communicate through Projected Visual Abstractions

arXiv:2607.22434v1 Announce Type: new Abstract: Humans routinely communicate through abstractions of their bodies, including shadows, silhouettes, and reflections. Yet robots remain largely confined t

researcharxiv-cs-ro

SCALE: Self-Supervised Constraint-Aware Layout GEneration for Local P&R DRV Fixing at Advanced Nodes

arXiv:2607.21850v1 Announce Type: new Abstract: As semiconductor manufacturing advances toward sub-2nm nodes, local place-and-route (P&R) design-rule violation (DRV) fixing is increasingly limited by

local-aiarxiv-cs-cv

SceneActBench: Can Agents Act on the 3D Scenes They See?

arXiv:2607.22393v1 Announce Type: cross Abstract: Vision-language model (VLM) agents increasingly use tools to act on 3D scenes rather than only describe them. Existing 3D benchmarks score textual res

Skill Self-Play: Pushing the Frontier of LLM Capability with Co-Evolving Skills

arXiv:2607.22529v1 Announce Type: new Abstract: LLM training is shifting from manual design and annotation to interaction-driven self-evolution. However, existing self-evolutionary methods face a fund

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images

arXiv:2607.22332v1 Announce Type: new Abstract: Interactive deep image segmentation enables efficient medical image annotation by iteratively refining predictions from user prompts, such as positive a

researcharxiv-cs-cv

Small context windows + knowledge graphs: the serialization format alone doubled my multi-hop accuracy (benchmarked 10 formats)

Running local models means every token counts — an 8K or 16K window fills up fast when you're stuffing graph context into prompts for RAG. I benchmarked 10 graph serialization formats (JSON, GraphML,

The Lift Spectrum: How Measurement-to-Space Adaptivity Shapes Robustness in Image-Free Single-Pixel Sensing

arXiv:2607.22077v1 Announce Type: cross Abstract: Single-pixel sensing encodes a scene as a short sequence of coded measurements, and image-free methods infer the task directly from that sequence. Rem

Time-Reversed Imaging: A Multimodal Benchmark and Framework for Reconstructing Past Human-Environment Interactions

arXiv:2607.22352v1 Announce Type: new Abstract: We introduce time-reversed imaging, a new paradigm that infers what just happened in a scene from fading multimodal traces. Instead of extrapolating or

Very cool paper from Microsoft. The idea is to train agents on replayed teacher trajectories instead of live environment rollouts. On-policy…

Very cool paper from Microsoft. The idea is to train agents on replayed teacher trajectories instead of live environment rollouts. On-policy distillation for agentic tasks is expensive because every u

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VTM-Nav: Harnessing Cross-Episode Experience for Object-Goal Navigation with Hierarchical Visual-Topological Memory

arXiv:2607.14514v2 Announce Type: replace Abstract: Training-free ObjectNav agents increasingly use vision-language models (VLMs), yet typically discard acquired scene knowledge after each request. We

agentsarxiv-cs-cv