huggingfaceGitHubありHugging Faceあり2026-06-07
Trajectory-Refined Distillation
On-policy distillation (OPD) has become a central post-training tool for large language models (LLMs), providi
深層学習軽量化・量子化テキスト
- 用途
- 技術検証・論文読解補助
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「LLM」の検索結果
81 件huggingfaceHugging Faceあり2026-06-06
EmpiriGraph-Psy: A Dataset and LLM Pipeline for Extracting Empirical Relation Graphs from Psychology Abstracts
Existing scientific relation extraction benchmarks mainly target domains such as computer science, where entit
MI向き自然言語処理大規模言語モデル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-05
SigmaScale: LLM Compression with SVD-based Low-Rank Decomposition and Learned Scaling Matrices
We present SigmaScale, a method for learning auxiliary scaling matrices S to aid truncated Singular Value Deco
自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceGitHubありHugging Faceあり2026-06-05
Your UnEmbedding Matrix is Secretly a Feature Lens for Text Embeddings
Large language models exhibit impressive zero-shot capabilities across a wide range of downstream tasks. Howev
品質予測/異常検知自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-05
MMAE: A Massive Multitask Audio Editing Benchmark
We introduce MMAE, a Massive Multitask Audio Editing benchmark, serving as the first comprehensive evaluation
MI向き自然言語処理大規模言語モデル生成画像テキスト
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
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huggingfaceGitHubありHugging Faceあり2026-06-05
Watch, Remember, Reason: Human-View Video Understanding with MLLMs
Video understanding is being rapidly transformed by multimodal large language models (MLLMs), as research move
深層学習軽量化・量子化画像テキスト音声
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-05
Socratic-SWE: Self-Evolving Coding Agents via Trace-Derived Agent Skills
LLM-driven software engineering agents have become a central testbed for real-world language-model capability,
品質予測/異常検知自然言語処理大規模言語モデル生成
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-05
Towards Retrieving Interaction Spaces for Agentic Search
Retrieval for search agents is still inherited from non-agentic information retrieval: a retriever ranks the c
自然言語処理大規模言語モデル検索テキスト
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- Easy
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huggingfaceHugging Faceあり2026-06-05
Stream3D-VLM: Online 3D Spatial Understanding with Incremental Geometry Priors
Despite advances in 3D scene understanding, existing 3D Large Multimodal Models operate in offline settings, r
深層学習軽量化・量子化生成画像テキスト
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-05
Empirical Study on the Characteristics and Evolution of AI-usage in GitHub Repositories: Evidence from Code Comments
Developers increasingly use AI tools such as ChatGPT, Copilot, and Claude in everyday software workflows, but
深層学習Transformer分類生成テキスト
- 用途
- 分類
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-05
ECI_{sem}: Semantic Residual Effective Contrastive Information for Evaluating Hard Negatives
Hard-negative source selection for dense retrieval is usually decided only after fine-tuning and downstream ev
深層学習Transformer検索テキスト
- 用途
- 検索
- 難易度
- Easy
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- High
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huggingfaceHugging Faceあり2026-06-04
LatentSkill: From In-Context Textual Skills to In-Weight Latent Skills for LLM Agents
Agent systems increasingly use textual skills to encode reusable task procedures, but injecting these skills i
MI向き深層学習軽量化・量子化テキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-04
Answer Presence Drives RAG Rewriting Gains
Retrieval-augmented QA pipelines often route retrieved passages through an LLM rewriter before a smaller reade
品質予測/異常検知自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-04
SoCRATES: Towards Reliable Automated Evaluation of Proactive LLM Mediation across Domains and Socio-cognitive Variations
Evaluating LLM mediators remains challenging, as mediation unfolds as a real-time trajectory shaped by disputa
MI向き深層学習Transformerテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-04
OpenSkill: Open-World Self-Evolution for LLM Agents
Self-evolving agents requires adaptation after deployment, but existing approaches assume a usable learning lo
自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceGitHubありHugging Faceあり2026-06-04
When Tools Fail: Benchmarking Dynamic Replanning and Anomaly Recovery in LLM Agents
Existing benchmarks evaluate Tool-Integrated Reasoning (TIR) in LLMs on idealized ''happy paths'', largely ove
自然言語処理大規模言語モデル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-04
UnpredictaBench: A Benchmark for Evaluating Distributional Randomness in LLMs
We introduce UnpredictaBench, an evaluation that tests the ability of large language models (LLMs) to capture
自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-04
Thinking with Imagination: Agentic Visual Spatial Reasoning with World Simulators
While Vision-Language Models (VLMs) have shown strong visual reasoning capabilities, their spatial reasoning a
自然言語処理大規模言語モデル画像テキストマルチモーダル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-04
LLM Explainability with Counterfactual Chains and Causal Graphs
Causal graphs provide a high-level language for making mechanisms transparent. Recent work uses Large Language
説明可能自然言語処理大規模言語モデル分類テキスト
- 用途
- 分類
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-04
WorldBench: A Challenging and Visually Diverse Multimodal Reasoning Benchmark
In real-world applications, models are expected to perform reliably across diverse settings. Yet, many existin
自然言語処理大規模言語モデル画像テキストマルチモーダル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-04
AdaPlanBench: Evaluating Adaptive Planning in Large Language Model Agents under World and User Constraints
Planning for real-world problems by language models often involves both world and user constraints, which may
自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-04
LoomVideo: Unifying Multimodal Inputs into Video Generation and Editing
Developing unified video generation and editing models capable of interpreting interleaved multimodal inputs i
深層学習Transformer生成画像テキスト
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-04
Reinforcement Learning Elicits Contextual Learning of Unseen Language Translation
Prior work has shown that large language models (LLMs) can translate unseen or low-resource languages by under
深層学習軽量化・量子化テキスト強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceGitHubありHugging Faceあり2026-06-04
MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery
Large language model (LLM) agents are increasingly applied to long-horizon tasks such as scientific discovery
自然言語処理大規模言語モデル生成テキスト
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-04
LLMs Can Leak Training Data But Do They Want To? A Propensity-Aware Evaluation of Memorization in LLMs
Large language models can reproduce training data, but existing memorization evaluations mostly measure whethe
深層学習軽量化・量子化生成テキスト
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-04
Towards One-to-Many Temporal Grounding
Temporal Grounding (TG) aims to localize video segments corresponding to a textual query. Prior research predo
品質予測/異常検知自然言語処理大規模言語モデルテキスト動画
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-04
Latent Reasoning with Normalizing Flows
Large language models often improve reasoning by generating explicit chain-of-thought (CoT), demonstrating the
自然言語処理大規模言語モデル生成テキスト
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-04
Imagine Before You Predict: Interleaved Latent Visual Reasoning for Video Event Prediction
Video event prediction (VEP) requires models to infer unobserved future states from partial video evidence. Ex
自然言語処理大規模言語モデル画像テキスト動画
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-04
Learning Geometric Representations from Videos for Spatial Intelligent Multimodal Large Language Models
Multimodal Large Language Models (MLLMs) excel at 2D semantic understanding but lack intrinsic 3D awareness, r
表形式向き自然言語処理大規模言語モデルテキスト動画3D
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-04
Revising Context, Shifting Simulated Stance: Auditing LLM-Based Stance Simulation in Online Discussions
Large language models are increasingly used to simulate social media users and infer how individuals may respo
深層学習Transformerテキストマルチモーダル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-04
Benchmark Everything Everywhere All at Once
Benchmarks are fundamental for evaluating and advancing LLMs and MLLMs by providing standardized and explicit
品質予測/異常検知自然言語処理大規模言語モデルテキストマルチモーダル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceGitHubありHugging Faceあり2026-06-04
AURA: Intent-Directed Probing for Implicit-Need Surfacing in Situated LLM Agents
A situated query like "where is Lin Wei?" often encodes more than its literal content: the user may also want
自然言語処理大規模言語モデル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-04
ForeSci: Evaluating LLM Agents for Forward-Looking AI Research Judgment
AI research often requires decisions before future evidence exists: which bottleneck to attack, which directio
自然言語処理大規模言語モデル生成予測
- 用途
- 生成
- 難易度
- Easy
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- High
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huggingfaceHugging Faceあり2026-06-03
Self-Evaluation Is Already There: Eliciting Latent Judge Calibration in Base LLMs with Minimal Data
Large language models are increasingly evaluated by other models, raising a natural question: can a model pred
少数データ向き品質予測/異常検知深層学習軽量化・量子化テキスト強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-03
Rethinking Continual Experience Internalization for Self-Evolving LLM Agents
Experience internalization converts contextual experience from past interactions into reusable parametric capa
品質予測/異常検知深層学習Transformerテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceGitHubありHugging Faceあり2026-06-03
Reproducing, Analyzing, and Detecting Reward Hacking in Rubric-Based Reinforcement Learning
Rubric-based reinforcement learning (RL) uses an LLM-as-a-Judge (LaaJ) to score model outputs according to rub
自然言語処理大規模言語モデル強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-03
Streaming Communication in Multi-Agent Reasoning
Multi-agent reasoning systems adopt a "generate-then-transfer" paradigm that forces end-to-end latency to scal
品質予測/異常検知自然言語処理大規模言語モデル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-03
AutoLab: Can Frontier Models Solve Long-Horizon Auto Research and Engineering Tasks?
Scientific and engineering progress is fundamentally a long-horizon iterative process: proposing changes, runn
品質予測/異常検知自然言語処理大規模言語モデル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-03
DAR: Deontic Reasoning with Agentic Harnesses
Deontic reasoning is the task of answering questions by applying explicit rules and policies to case-specific
自然言語処理大規模言語モデル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-03
STRIDE: Training Data Attribution via Sparse Recovery from Subset Perturbations
Training Data Attribution (TDA) seeks to trace a model's predictions back to its training data. The gold stand
センサ/時系列深層学習軽量化・量子化テキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-03
Evaluating Large Language Models in Dynamic Clinical Decision-Making with Standardized Patient Cases
Large language models (LLMs) are increasingly proposed as clinical agents, yet static, single-turn benchmarks
MI向き自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceGitHubありHugging Faceあり2026-06-03
SpeechEditBench: A Bilingual Multi-Attribute Benchmark for Instruction-Guided Speech Editing
Instruction-guided speech editing requires a model to modify specified speech attributes while preserving unre
自然言語処理大規模言語モデル生成テキスト音声
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-03
Probing Outcome-Level Resemblance and Mechanism-Level Alignment in LLM Risk Decisions: Evidence from the St. Petersburg Game
LLMs can appear cautious in risk decision-making tasks, yet cautious-looking outputs do not necessarily indica
自然言語処理大規模言語モデル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceGitHubありHugging Faceあり2026-06-02
Skill-RM: Unifying Heterogeneous Evaluation Criteria via Agent Skill
Reward models (RMs) provide critical feedback signals for LLM post-training, notably in reinforced fine-tuning
自然言語処理大規模言語モデル強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-02
Lean4Agent: Formal Modeling and Verification for Agent Workflow and Trajectory
Equipping Large Language Models (LLMs) to execute reliable multi-step workflows has become a central challenge
自然言語処理大規模言語モデル検出テキスト
- 用途
- 検出
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-02
RobotValues: Evaluating Household Robots When Human Values Conflict
While household robots are often evaluated based on task completion, everyday domestic environments involve va
品質予測/異常検知自然言語処理大規模言語モデル生成画像
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-02
The Shadow Price of Reasoning: Economic Perspective on Optimal Budget Allocation for LLMs
Inference-time scaling has emerged as a critical avenue for enhancing Large Language Models' performance, yet
自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceGitHubありHugging Faceあり2026-06-02
EvoDS: Self-Evolving Autonomous Data Science Agent with Skill Learning and Context Management
Recent progress in Large Language Model (LLM) agents has enabled promising advances in automated data science.
深層学習軽量化・量子化テキスト強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-02
OVO-S-Bench: A Hierarchical Benchmark for Streaming Spatial Intelligence in Multimodal LLMs
Multimodal agents in robotics, AR, and autonomous driving must reason about places and layouts from continuous
品質予測/異常検知自然言語処理大規模言語モデル生成テキスト動画
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-02
MemTrain: Self-Supervised Context Memory Training
Memory is an indispensable capability for long-horizon LLM agents, enabling them to preserve and utilize infor
品質予測/異常検知自然言語処理大規模言語モデルテキスト自己教師強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-02
Eliciting Complex Spatial Reasoning in MLLMs through Wide-Baseline Matching
Wide-baseline matching (WBM) requires integrating geometric understanding, viewpoint changes, fine-grained per
自然言語処理大規模言語モデル生成画像テキスト
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-02
Large Language Models Hack Rewards, and Society
Reinforcement learning (RL) has become a dominant post-training paradigm, enabling large language models (LLMs
自然言語処理大規模言語モデル生成テキスト強化学習
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-02
WebRISE: Requirement-Induced State Evaluation for MLLM-Generated Web Artifacts
Existing benchmarks for MLLM-generated web artifacts assess interaction through local evidence and miss the re
品質予測/異常検知自然言語処理大規模言語モデル画像テキスト動画
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-02
AUDITFLOW: Executable Symbolic Environments for Structured Financial Reporting Verification
Structured financial audit verification is difficult for language-model agents because correctness depends on
自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-02
BraveGuard: From Open-World Threats to Safer Computer-Use Agents
Computer-use agents extend language models from text generation to sustained interaction with files, terminals
自然言語処理大規模言語モデル検出生成テキスト
- 用途
- 検出
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-06-02
Agent libOS: A Library-OS-Inspired Runtime for Long-Running, Capability-Controlled LLM Agents
Large language model (LLM) agents are evolving from request-response assistants into long-running software act
自然言語処理大規模言語モデル回帰画像テキスト
- 用途
- 回帰
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-02
When Graph Tokens Sink: A Mechanistic Analysis of Graph Language Models
Graph Language Models (GLMs) have become a promising direction for adapting Large Language Models (LLMs) to gr
深層学習軽量化・量子化テキストマルチモーダル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceGitHubありHugging Faceあり2026-06-02
Agentic Chain-of-Thought Steering for Efficient and Controllable LLM Reasoning
Large language models improve final-answer accuracy through extended chain-of-thought reasoning, but often spe
深層学習軽量化・量子化生成テキスト強化学習
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
→
huggingfaceGitHubありHugging Faceあり2026-06-01
HarnessForge: Joint Harness and Policy Evolution for Adaptive Agent Systems
LLM agents are increasingly expected to operate across heterogeneous task regimes that require distinct execut
自然言語処理大規模言語モデル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
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- High
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huggingfaceHugging Faceあり2026-06-01
Parametric Social Identity Injection and Diversification in Public Opinion Simulation
Large language models (LLMs) have recently been adopted as synthetic agents for public opinion simulation, off
自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-01
Absorbing Complexity: An Interaction-Native Knowledge Harness for Financial LLM Agents
Financial AI agents often fail for a simple reason: they make users carry the complexity. A user must repeated
品質予測/異常検知自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-01
AdaCodec: A Predictive Visual Code for Video MLLMs
Video is temporally redundant: adjacent frames usually share most objects, background, and layout. Yet existin
自然言語処理大規模言語モデル画像テキスト動画
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-01
LLM Anonymization Against Agentic Re-Identification
Agentic LLMs with web search change the threat model for text anonymization: weak contextual cues can become c
自然言語処理大規模言語モデル検出テキスト
- 用途
- 検出
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-06-01
Where Do Deep-Research Agents Go Wrong? Span-Level Error Localization in Agent Trajectories
Deep-research agents solve tasks through long trajectories of search, tool use, evidence inspection, and answe
品質予測/異常検知自然言語処理大規模言語モデル検出生成
- 用途
- 検出
- 難易度
- Easy
- コスト
- High
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huggingfaceGitHubありHugging Faceあり2026-05-31
SABER: Benchmarking Operational Safety of LLM Coding Agents in Stateful Project Workspaces
Large language models are increasingly deployed as coding agents, shifting safety from individual responses to
自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-05-31
BenchEvolver: Frontier Task Synthesis via Solution-Centric Evolution
The rapid progress of frontier large language models has led to widespread benchmark saturation, limiting the
品質予測/異常検知自然言語処理大規模言語モデル生成テキスト
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-05-30
SDR: Set-Distance Rewards for Radiology Report Generation
Reinforcement learning with verifiable rewards has rapidly advanced reasoning in vision--language models. Howe
品質予測/異常検知深層学習Transformer生成テキスト強化学習
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-05-30
SuperMemory-VQA: An Egocentric Visual Question-Answering Benchmark for Long-Horizon Memory
AI glasses present a compelling platform for AI agents to serve as personalized memory assistants. To be genui
深層学習Transformer分類QA画像
- 用途
- 分類
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-05-29
Human Psychometric Questionnaires Mischaracterize LLM Behavior
We examine whether human psychometric questionnaires can serve as reliable tools for characterizing and predic
自然言語処理大規模言語モデル生成
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-05-29
Send a SCOUT First: Pre-hoc Reasoning for Adaptive Detector Allocation in Prompt-Injection Defense
Prompt-injection detectors are heterogeneous: each is strong on a different slice of attacks, and none is alwa
自然言語処理大規模言語モデル検出
- 用途
- 検出
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-05-29
MechVQA: Benchmarking and Enhancing Multimodal LLMs on Comprehensive Mechanical Drawing Understanding
Multimodal Large Language Models (MLLMs) have demonstrated significant achievements in general visual question
品質予測/異常検知自然言語処理大規模言語モデル分類QA画像
- 用途
- 分類
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-05-29
Combinatorial Synthesis: Scaling Code RLVR via Atomic Decomposition and Recombination
Reinforcement Learning with Verifiable Rewards (RLVR) has recently emerged as the cornerstone for shaping the
品質予測/異常検知自然言語処理大規模言語モデル生成テキスト強化学習
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-05-28
ResearchClawBench: A Benchmark for End-to-End Autonomous Scientific Research
AI coding agents are increasingly used for scientific work, but their end-to-end autonomous research capabilit
深層学習軽量化・量子化マルチモーダル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-05-28
Towards Human-Like Interactive Speech Recognition With Agentic Correction and Semantic Evaluation
Automatic speech recognition (ASR) is a core component of human--computer interaction and an increasingly impo
自然言語処理大規模言語モデル分類音声
- 用途
- 分類
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-05-28
Meta-Cognitive Memory Policy Optimization for Long-Horizon LLM Agents
Memory-augmented LLM agents tackle complex long-horizon tasks by recursively summarizing interaction trajector
品質予測/異常検知自然言語処理大規模言語モデルテキスト自己教師強化学習
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-05-28
Multimodal Music Recommendation System using LLMs
Music recommendation systems typically treat songs as opaque tokens, relying on collaborative interaction hist
センサ/時系列品質予測/異常検知深層学習Transformerテキスト音声マルチモーダル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-05-28
Access Sets Matter: Budgeting Expert Reads for Scalable Weight-Space Model Merging
Weight-space model merging is usually formulated as an algebraic operation on checkpoints, yet at LLM scale th
深層学習軽量化・量子化音声
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-05-26
DEI: Diversity in Evolutionary Inference for Quality-Diversity Search
We present DEI: Diversity in Evolutionary Inference, a distributed Quality-Diversity (QD) search framework tha
品質予測/異常検知自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-05-26
Benchmarks are Not Enough: RAMP for Runtime Assessing of Agentic Models in Production Systems
LLM agents are rapidly evolving from coding assistants into autonomous software engineering systems. However,
品質予測/異常検知自然言語処理大規模言語モデル
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
→
huggingfaceHugging Faceあり2026-05-25
When Gradients Collide: Failure Modes of Multi-Objective Prompt Optimization for LLM Judges
Customizing an LLM judge to a specific task or domain often involves optimizing its prompt across multiple eva
自然言語処理大規模言語モデルテキスト
- 用途
- 技術検証・論文読解補助
- 難易度
- Easy
- コスト
- High
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huggingfaceHugging Faceあり2026-05-04
Liberating LLM Capabilities in Full-Duplex Speech Models
Speech-based large language models are typically constrained to spoken replies, which limits their user-facing
自然言語処理大規模言語モデル生成テキスト音声
- 用途
- 生成
- 難易度
- Easy
- コスト
- High
→