「SHAP」の検索結果
110 件As deep learning (DL) models become increasingly complex and hardware architectures grow more heterogeneous, D
What makes a pretraining corpus transferable? We describe a corpus by three properties: its structure, its dim
Medicinal plants are usually identified using practitioners' experience, but reproducible, image based methods
Inoculation prompting is a method to reduce undesired behaviours such as reward hacking in frontier models. It
Large language models (LLMs) increasingly shape recommendations across chatbots, e-commerce, and user-generate
Harnesses for large language models have converged on a single-threaded shape: one agent, one history, one mac
機械学習モデルの出力を説明するゲーム理論的手法を取ったライブラリ。
We study the problem of average reward Multi-Agent Reinforcement Learning (MARL) where agents interact within
Large foundation models often answer even when the available visual or textual evidence is insufficient to sup
Reinforcement learning with verifiable rewards (RLVR) can enable generalizable improvement for large language
In the near future language model pretraining will become bound by total data rather than total compute. Such
Recent language model (LM) safety failures have largely been studied as disparate phenomena. In agentic misali
Suicide prevention remains a critical public health challenge, and electronic health records (EHRs) provide an
Open multi-agent systems, where only a subset of agents are controllable, are central to real-world domains su
There are many causal discovery algorithms, but few guiding principles for choosing between them. Methods are
Generative search engines increasingly shape how users discover products, services, and commercial entities by
Next-generation open radio access network (Open RAN) and AI-RAN deployments turn the RAN into a disaggregated,
Technology-mediated audience participation (TMAP) enables audiences to influence live performances, yet balanc
A memory-augmented agent must decide which memories to keep, merge and retrieve, and its only evidence of thei
Online political discussions increasingly involve AI-mediated participation, as users invoke LLMs to assess co
AI scientists are expanding automated research across scientific domains, yet their ability to turn the scient
Interactive narratives let users shape a story while an Experience Manager (EM) keeps it coherent, balancing p
Interactive narratives aim to let players influence the unfolding of a story while preserving a coherent and s
Law changes over time. A court decides a case under the law in force on that day, and legal QA benchmarks grad
Research taste, the judgment of what to read, which problems to pursue, and which methods to try, increasingly
The widespread adoption of Large Language Models (LLMs) demands reliable detection of human-authored versus sy
Generating visualisations from natural language requests (text-to-vis) enables users to explore data more effi
Text-to-CAD generation aims to make CAD modeling more accessible by generating executable CAD programs from na
Parametric human body models such as the Skinned Multi-Person Linear (SMPL) model provide compact representati
Fingerspelling - the sequential signing of letters that compose proper names, technical terms, and out-of-voca
Quantum-inspired computer vision often reshapes high-dimensional features into tensors and applies tensor-netw
Reinforcement learning (RL) post-training improves the single-sample quality of visual generative models, but
In robotics, shape control, or shape servoing, refers to the automatic manipulation of a deformable object tow
This work investigates human-swarm interaction (HSI) for steering large collectives through an intermediary ro
Conventional robot arms can be extremely heavy compared with the everyday objects they manipulate, creating a
Myoelectric Control Systems (MCSs) enable voluntary control of wearable robots through muscle activity. Howeve
This paper presents a decentralized guiding vector field framework for rigid formation path following in multi
Edge computing service deployment requires the Network Operator (NO) and Service Providers (SPs) to coordinate
This paper proposes a cooperative game-theoretical framework for the financial settlement of real-time deviati
Language and vision models became data-efficient by pretraining on plentiful unlabelled data; physical field m
Convex regression provides a flexible nonparametric estimation framework while incorporating appropriate shape
An input guard decides whether a request reaches the model, but never sees what the model says. Harm that emer
Linear recurrences are becoming an increasingly common building block in large language models, replacing the
LLM-based role-playing agents are fluent at imitating a character's style, yet struggle to make role-consisten
Goal pursuit in open-ended dialogue requires agents to adapt their actions to interaction feedback across succ
Concerns about LLM homogeneity are typically quantified with embedding similarity, which reduces two texts to
The widespread adoption of large language models (LLMs) is reshaping how textual content is produced, complica
Reinforcement learning with verifiable rewards (RLVR) has become an effective post-training paradigm for visio
Recent advances in generative AI have enabled multiple pathways for high-fidelity video synthesis: text-to-vid
Coding agents solve repository issues through long sequences of exploration, editing, and validation. These tr
Across diverse markets, it is important for firms to balance attracting customers with managing operational co
Surprisal correlates closely with reading time and is widely used in the cognitive science of reading as a mea
What happens when language models are given tools to iteratively modify their own system prompts? We present a
Exploring systems that bridge the gap between non living and living matter requires a reconfigurable environme
The MetaFine Open Competition (RoboFineMani workshop, CoRL 2026) evaluates fine-grained manipulation beyond bi
Accurate posture feedback is essential for precise control of continuum robots. Off-the-shelf bend sensors mea
Performativity arises when prediction-informed decisions change the data-generating process, creating feedback
Can a vision-language-action (VLA) policy signal likely task failure from its own action probabilities? We int
Humanoid controllers have acquired increasingly diverse motor skills, yet translating these capabilities into
A fallen humanoid beneath an overhead obstacle faces a coupled recovery problem. It must create clearance whil
Robotic Manipulation Surfaces (RMS) reposition objects by deforming the surface on which they rest. A recent c
Inserting an unseen part requires sub-millimetre precision and the correct orientation of keyed features. Curr
Architectural spaces are increasingly gaining robotic capabilities. Architectural robots such as robotic parti
Recent advances in generative foundation models have expanded the capabilities of embodied AI, enabling increa
Wearable force-augmentation technologies, including exoskeletons and soft exosuits, are being developed for oc
Reinforcement learning and game theory describe the same object from two sides. Game theory says what a ration
Statistical contracts reward experimenters according to the evidence produced by a costly study, so the reward
Linear attention scales linearly with sequence length, but its finite-state memory can limit long-context retr
Continuous relaxations are commonly used as an encoding scheme for evolutionary multitasking optimization (EMT
Hardware-accelerated spiking neural networks (SNNs) implemented on memristive crossbar arrays offer significan
In a duopoly with captive and contested consumers, I characterize every pair of consumer and producer surplus
Training acceleration methods for diffusion transformers, such as REPA and dispersive regularization, are comm
This work investigates device-informed spike-timing-dependent plasticity (STDP) in spiking neural networks usi
Bisimulation metrics offer a principled notion of task-relevant state similarity in reinforcement learning, bu
Generative flows can admit different velocity fields that induce the same continuous marginal evolution but be
In this paper, we introduce a model-based boosting approach for fitting structured additive distributional cop
Recent work has shown that, in zero-sum games, an optimizer can extract $Ω(\sqrt{T})$ strategic surplus---cumu
Large Language Models (LLMs) are increasingly used in multi-turn agentic workloads that require sustained inte
Spiking neural networks (SNNs) encode information not only in whether neurons fire but also in when they fire,
We study how learning algorithm design shapes equilibrium selection in infinite-horizon discounted Markov game
Shapley-value-based explanations are widely used for feature attribution in machine learning. However, in comp
In token-priced language model services, users can see the prompts they submit and the answers they receive, b
The quality with which language models follow instructions falls as the load grows, yet there is still no quan
As AI agents reshape Web search and advertising, platforms can monetize information that improves decisions. W
Language agents increasingly act through external tools and interactive environments, making the interface bet
Do preferences Large Language Models (LLMs) express in standard elicitation tasks predict their strategic beha
Attribution for a time-series forecaster should answer two questions that a feature-level scalar cannot: when
A common measure of the quality of a voting rule is the social welfare of the alternatives it elects. Prior wo
Recommender systems typically serve one user at a time. However, in households, members share a finite pantry
Generative AI assistants are becoming an advertising medium, embedding sponsored content in their answers. Thi
Blockchain participation games combine costly entry, random participation selection, and threshold success int
Language-model agents are increasingly deployed to act on behalf of people in settings where individual decisi
Digital marketplaces increasingly earn revenue from transaction commissions and seller-facing data services. S
Our understanding of turn-based stochastic games is reminiscent of our understanding of linear programming in
Repeated Bertrand competition is a stringent benchmark for algorithmic pricing: in homogeneous-goods markets,
Despite their practical significance, modern AI systems pose significant societal risks, including toxicity, m
Mandlebrot's coastline paradox reframes measurement as a joint property of an object and its ruler. Here we as
Assigning routine tasks to cheaper large language model (LLM) providers can reduce generation cost, but switch
Freshness shapes an LLM decision at the moment it is made; the action it commits to is latent, carried out lat
Plurality-voting ensembles aggregate the predictions of multiple base classifiers and output the most voted cl
We investigate the growth trajectory of online platforms operating as market makers in two-sided matching mark
Black-box optimization (BBO) arises in many scientific and engineering problems where objective evaluations ar
Genetic programming was conceived as a way of evolving solutions: the program is the answer, and fitness is th
Where generalization capacity--the ability to extract context-invariant relational structures--first emerges r
Segment-based explanation methods such as LIME return a single explanation for each prediction, computed from
As Artificial Intelligence (AI) has evolved from task-specific models to foundation models and agents, the sco
Learning can improve an individual's behavior, yet a population risks losing that experience whenever individu
How search strategies evolve in finite, depletable landscapes remains a question in foraging theory. We study
Hyperdimensional computing and vector symbolic architectures often represent quantized scalar levels by dense
We study the knowledge matrix of a trained feedforward network as a higher representation of its inputs. A net