Search: “agents”

GRID-Planner: Graph-Structured Relational Reward Shaping for Diffusion Planning

arXiv:2610.21984v1 Announce Type: cross Abstract: Autonomous driving planning requires selecting trajectories that remain safe, rule-compliant, and comfortable under complex multi-agent interactions,

safetyarxiv-cs-cv

Human

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Research

Love for Believable AI: Artificial Partiality and Relationship Persistence as an Engineerable Stance

DGX agent

arXiv:2610.09895v1 Announce Type: cross Abstract: We study a behavioral mechanism for artificial partiality in conversational agents. The paper reports no human-subjects data and makes no claim about

researcharxiv-cs-cl

16 Oct 2026

Mem4Act: Learning Effective Latent Memory for Long-Horizon Robotic Manipulation

arXiv:2610.22323v1 Announce Type: new Abstract: Long-horizon robotic manipulation fundamentally requires memory: agents must retain task-relevant information from past observations and interactions an

safetyarxiv-cs-ro

Hardware

MJev-Spatial: System One Spatial Intelligence via Native Attention Matching

arXiv:2610.22276v1 Announce Type: new Abstract: Spatial intelligence lets an agent perceive and act in the physical world, and many of its judgments must be made at interaction rates: which spatial re

hardwarearxiv-cs-cv

Planning Commitment of LLM under Partial Observability

arXiv:2610.21108v1 Announce Type: new Abstract: LLM-based planning agents commit to plans of different lengths before interacting with a partially observable environment. Some aggressively commit to a

Poison Valleys: Diagnosing Path-Dependent Failure in LLM Code Repair

arXiv:2610.21514v1 Announce Type: cross Abstract: When code-repair agents fail, final tests reveal that a patch is wrong but not which earlier commitment caused it or which software obligation failed.

researcharxiv-cs-ai

Progress Reward Model for Reinforcement Learning via Large Language Models

arXiv:2610.22056v1 Announce Type: new Abstract: Traditional reinforcement learning (RL) algorithms face significant limitations in handling long-term tasks with sparse rewards. Recent advancements hav

RAG-RST: Retrieved Exemplars as In-Context Discourse Schema for RST Parsing

arXiv:2610.22150v1 Announce Type: new Abstract: In Rhetorical Structure Theory (RST), each edge of a discourse tree carries a nuclearity label, marking which span holds the central content, and a rela

SHRED: Self-Play for Heterogeneous Road-Users without Expert Demonstrations

arXiv:2610.20866v1 Announce Type: cross Abstract: Realistic traffic simulation and autonomous planning both depend on modeling interactions among heterogeneous road users whose dynamics, constraints,

Stop Training Against Soft Users: Mentalized Adversarial Self-Play for Proactive Dialogue

arXiv:2610.21156v1 Announce Type: new Abstract: Proactive dialogue agents must guide multi-turn interactions toward task goals while adapting to users whose intentions and attitudes evolve. Existing p

safetyarxiv-cs-cl

Tool-Augmented Large Language Models for Reliable Medical Calculation from Patient Notes

arXiv:2610.21477v1 Announce Type: new Abstract: Medical calculators translate raw patient observations into clinically actionable values and scores. However, applying these calculators directly to fre

X-Fly: Learning to Reach and Stop in Full-Chunk Aerial Vision-Language Navigation

arXiv:2610.21450v1 Announce Type: cross Abstract: Aerial vision-language navigation (VLN) agents built on large vision-language models are expensive to query. Executing a complete predicted action chu

Accelerating the search for antimicrobial peptides with Google Antigravity

model-releasesgoogle-deepmind

Google Antigravity is an agentic science workbench that consolidates multiple biological databases into a single interface, enabling biologists to rapidly discover, evaluate, and prioritize therapeuti

Beyond Successful Play: Diagnosing Opponent Modeling in Large Language Models

arXiv:2610.17310v1 Announce Type: new Abstract: Language-model agents are expected to adapt to others whose behavior changes through interaction. Yet adaptation may rely on learned behavioral patterns

Budgeted KV-Cache Repair for Evolving Contexts

arXiv:2610.17338v1 Announce Type: new Abstract: Language-model agents revise their working context as information becomes obsolete, but deleting text does not erase its influence on cached computation

researcharxiv-cs-ai

Local Ai

Calibration and Risk-Budgeted Decisions with System One Models

arXiv:2610.19811v1 Announce Type: cross Abstract: LLM workflows and agents rely on a set of binary decisions like allow/block an input, or discard/retain a retrieved document. When human deferral is u

local-aiarxiv-cs-lg

Certifying Almost-Sure Reachability in Unknown MDPs

arXiv:2610.18119v1 Announce Type: cross Abstract: {em Specification-Guided Reinforcement Learning (RL)} has largely concerned itself with learning an optimal policy against a formal specification in a

Designing Textual Interfaces To Enhance Llm Reasoning On Audio-Visual Question Answering

model-releasesarxiv-cs-cl

arXiv:2610.20085v1 Announce Type: cross Abstract: Automatic prompt optimization (APO) has shown strong effectiveness for text-based LLMs and LLM systems, but its application to audio-visual understand

GroundGUI: GUI Grounding by High-Quality Data and Distillation-to-Reinforcement Learning

arXiv:2610.19100v1 Announce Type: cross Abstract: Constructing robust GUI agents relies on multimodal visual grounding: the ability to precisely map natural language intents to actionable on-screen co

researcharxiv-cs-cl

GUIDE: Computationally Augmented Consensus for Trustworthy Clinical Practice Guidelines

arXiv:2610.16108v1 Announce Type: new Abstract: Maintaining up-to-date clinical practice guidelines (CPGs) is essential for evidence-based medicine, but rapid evidence growth and complex expert consen

Harnesses + smart models = the end of the last famous hard benchmarks. Models can now work for extremely long times (bye, METR Long Tasks), …

model-releasesethan-mollick--x

Harnesses + smart models = the end of the last famous hard benchmarks. Models can now work for extremely long times (bye, METR Long Tasks), they can output professional documents with correct math (so

Learning in Strategic Queuing with Geometric Recharge: From Bandits to Systems

arXiv:2610.19179v1 Announce Type: cross Abstract: We study packet routing in queuing systems where queues act as selfish, myopic agents that use no-regret learning algorithms to select servers with un

Meta releases Muse Spark Open, saying it is the most capable US open-weight model, with 816B total and 42B active parameters and a 1M-token context window (Meta AI Research)

Meta AI Research: Meta releases Muse Spark Open, saying it is the most capable US open-weight model, with 816B total and 42B active parameters and a 1M-token context window — Muse Spark Open is availa

model-releasestechmeme

nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB · Hugging Face

model-releasesr-localllama

https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-GGUF https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-LiLiCorr-GGUF NVIDIA Nemotron 3.5 Bolt 74B-A9B 24GB is a vi

Industry

OpenAI continues to work to grow its ad business in ChatGPT, cutting ad rates, chasing small and midsize businesses, and hiring some new talent from Meta (Alix Coutures/The Information)

Alix Coutures / The Information: OpenAI continues to work to grow its ad business in ChatGPT, cutting ad rates, chasing small and midsize businesses, and hiring some new talent from Meta — As OpenAI h

industrytechmeme

Outperforming 1000 Euclidean Layers With Hyperbolic Goal-Conditioned RL

arXiv:2610.20009v1 Announce Type: new Abstract: Scaling self-supervised contrastive reinforcement learning (CRL) to 1000-layer Euclidean neural networks has enabled state-of-the-art goal-reaching perf

Industry

Q&A with Dwarkesh Patel on his podcast, lessons from history, AGI, the mood in San Francisco, the Hugging Face hack, Chinese AI, pacing the frontier, and more (New York Times)

New York Times: Q&A with Dwarkesh Patel on his podcast, lessons from history, AGI, the mood in San Francisco, the Hugging Face hack, Chinese AI, pacing the frontier, and more — Dwarkesh Patel on what

industrytechmeme

Recursive Improvement of a Differentiable Scientific Software Ecosystem

arXiv:2610.04561v2 Announce Type: replace Abstract: Differentiable programming connects scientific computation with gradient-based inference, learning and design. Extending these capabilities across a

StateCraft: Augmenting Video World Models with Abstract-State Reasoning

model-releasesarxiv-cs-cv

arXiv:2610.19795v1 Announce Type: new Abstract: Video world models aim to simulate complex environments with realistic appearance and dynamics. Maintaining consistency over long interactions requires

Towards a Data-Centric Understanding of Spatial Reasoning in Multimodal Large Language Models

model-releasesarxiv-cs-cl

arXiv:2610.19108v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have been widely applied in embodied agents and robotics for vision tasks. However, MLLMs suffer from limitat

v0.40.5

model-releasesollama-releases

NVIDIA Nemotron 3.5 Super NVIDIA Nemotron 3.5 Super is a vision-language model for coding, reasoning, tool use, and document understanding. It pairs a 120B-parameter hybrid Mamba-2/Transformer mixture

v0.7.0

model-releasesllama-cpp-releases

Overview llama.cpp v0.7.0 adds the LiliCorr speculative decoding technique and MTP for GLM5-Next, a new GPU cache for MoE experts kept in host memory (--moe-cache-mib, up to ~2.2x decode speedup when

When and How Order-Flow Interventions Work After Dealers Adapt

arXiv:2610.18158v1 Announce Type: new Abstract: Learning dealer agents can settle on persistently wide quotes, raising what customers pay to trade. A venue can route more orders to tighter quotes, but

A Hardware-Partitioned micro-ROS Mini-Vehicle for Operator-Supervised Neural Driving

arXiv:2610.15966v1 Announce Type: new Abstract: We present a low-cost miniature Ackermann vehicle for embedded neural-driving research, organized as a hardware-partitioned perceive-decide-act agent: a

safetyarxiv-cs-ro

AlignPred: Error-Controlled KV Cache Compression via Alignment and Predictive Coding

arXiv:2610.17970v1 Announce Type: cross Abstract: Long-running agents retain KV caches across turns and sessions for hours or days. Compressing these persistent caches requires reducing storage while

Auditing LLM Program Search for Bermudan Stopping with Primal--Dual Certificates

arXiv:2610.14063v1 Announce Type: new Abstract: LLM program-search agents are usually judged by the score that drives their search. We study LLM-driven search over Python exercise policies for Bermuda

Belief Embedding Tree Search

arXiv:2610.15046v1 Announce Type: cross Abstract: Beliefs in a Partially Observable Markov Decision Process (POMDP) are posterior distributions over the hidden state given the agent's history of actio

CFG-Policy: Unified Diffusion Policy Learning Framework via Classifier-free Guidance

arXiv:2610.14936v1 Announce Type: cross Abstract: Diffusion policies are increasingly used in robotic control and manipulation, vision-language-action models, and world-model-based agents. Their abili

CodeLift: Your Test Suite Is Secretly a Dense SWE Curriculum

arXiv:2610.17224v1 Announce Type: new Abstract: The pass-all-test binary reward has become a standard recipe for training software engineering agents, but its sparsity eliminates difference of partial

researcharxiv-cs-lg

Conditional Multi-Event Temporal Grounding in Long-Form Video

model-releasesarxiv-cs-cv

arXiv:2606.15320v2 Announce Type: replace Abstract: Multimodal large language models have made rapid progress in video temporal grounding, yet real-world applications routinely require localizing ever

Context-Aware Precision Scheduling for Small Language Models

model-releasesarxiv-cs-lg

arXiv:2610.15640v1 Announce Type: new Abstract: Small language models (SLMs) used as on-device agents must balance accuracy and latency as their context grows. Mixed precision helps manage this tradeo

Decentralized Bandit Learning of Markov Perfect Equilibria

arXiv:2610.14333v1 Announce Type: new Abstract: We study decentralized bandit learning in discounted infinite-horizon, general-sum Markov games with continuous actions. Agents observe the public state

researcharxiv-cs-lg

From Enterprise to Earthshot: UK’s Ecosystem Moves From Ambition to Application With NVIDIA

Across industries, the U.K. is putting the full stack to work — and the scale of deployment is growing fast, from enterprises transforming their businesses to startups solving some of the planet’s har

safetynvidia-blog

GIFT-Eval-CTX: A Benchmark For Contextual Forecasting Model Evaluation

model-releasesarxiv-cs-lg

arXiv:2610.17794v1 Announce Type: new Abstract: Contextual forecasting seeks to improve time series forecasting by incorporating forward-looking information, such as planned events, external condition

Learning Dynamic Grasping

arXiv:2610.14848v1 Announce Type: new Abstract: Synthesizing believable 4D hand-object grasping sequences is important for character animation, extended reality, and embodied agents. Grasping requires

researcharxiv-cs-ro

Learning to See through Action: Predictive Curiosity for Robots

arXiv:2610.14302v1 Announce Type: new Abstract: Humans and animals do not learn vision from a fixed set of data: they move, interact, and learn from the visual consequences of their actions. Motivated

MHVF: Training-Free GUI Grounding via Verification-Guided Multi-Hypothesis Search

model-releasesarxiv-cs-cv

arXiv:2610.17792v1 Announce Type: new Abstract: GUI grounding enables web agents to translate natural-language instructions into actionable interface locations. However, dense layouts and small, visua

Neural Bayesian Networks for Modular and Scalable Decision-Making Under Uncertainty

model-releasesarxiv-cs-lg

arXiv:2610.16902v1 Announce Type: cross Abstract: Bayesian Networks (BNs) are established tools for letting agents reason under uncertainty in sequential decision-making. They split a joint distributi