◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Masashi Sugiyama

8 papers hereh-index 3132 citations9 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author6
  • last author1

Across the 7 of 8 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.AI2
  • cs.CL1
  • cs.CR1
same name
  • Masashi Sugiyama — 250 papers, h 88
  • Masashi Sugiyama — 18 papers, h 7
  • Masashi Sugiyama — 9 papers, h 3
  • Masashi Sugiyama — 7 papers, h 4
  • Masashi Sugiyama — 7 papers, h 1
  • Masashi Sugiyama — 6 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedSafety at Scale: A Comprehensive Survey of Large Model and Agent Safety

1 citations · 1 across the 6 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026

Preemptive LLM Unlearning against Forbidden Capability Acquisition via Gradient Sealing

Kemou Li, Qizhou Wang, Yue Wang +6

Open-weight LLMs are released not only as fixed products but also as substrates for downstream fine-tuning. This openness, however, creates legal and ethical risks because users ma…

cs.LG2026

BrokenBind: Universal Modality Exploration beyond Dataset Boundaries

Zhuo Huang, Runnan Chen, Bo Han +3

Multi-modal learning combines various modalities to provide a comprehensive understanding of real-world problems. A common strategy is to directly bind different modalities togethe…

cs.LG2026

Bifrost: Steering Strategic Trajectories to Bridge Contextual Gaps for Self-Improving Agents

Quan M. Tran, Zhuo Huang, Wenbin Zhang +4

Autonomous agents excel in self-improvement through reflection and iterative refinement, which reuse successful task trajectories as in-context examples to assist subsequent reason…

cs.LG2025

Reinforcement Learning with Verifiable yet Noisy Rewards under Imperfect Verifiers

Xin-Qiang Cai, Wei Wang, Feng Liu +3

Reinforcement Learning with Verifiable Rewards (RLVR) replaces costly human labeling with automated verifiers. To reduce verifier hacking, many RLVR systems binarize rewards to $\{…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.