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Dispersion Loss Counteracts Embedding Condensation and Improves Generalization in Small Language Models
Paper • 2602.00217 • Published • 1 -
Staying VIGILant: Mitigating Visual Laziness via Counterfactual Visual Alignment in MLLMs
Paper • 2606.26387 • Published • 1 -
Creativity or Brute Force? Using Brainteasers as a Window into the Problem-Solving Abilities of Large Language Models
Paper • 2505.10844 • Published -
CTR-LoRA: Curvature-Aware and Trust-Region Guided Low-Rank Adaptation for Large Language Models
Paper • 2510.15962 • Published
Chen Liu
ChenLiu1996
AI & ML interests
None yet
Recent Activity
upvoted a paper 5 days ago
Deep Search in Real-World Web Environments upvoted a paper 10 days ago
Pack Light, CarryOn: Building Object-Oriented Context for Long-Horizon Agents authored a paper 14 days ago
Not All Directions Matter: Towards Structured and Task-Aware Low-Rank Model AdaptationOrganizations
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Dispersion Loss Counteracts Embedding Condensation and Improves Generalization in Small Language Models
Paper • 2602.00217 • Published • 1 -
Staying VIGILant: Mitigating Visual Laziness via Counterfactual Visual Alignment in MLLMs
Paper • 2606.26387 • Published • 1 -
Creativity or Brute Force? Using Brainteasers as a Window into the Problem-Solving Abilities of Large Language Models
Paper • 2505.10844 • Published -
CTR-LoRA: Curvature-Aware and Trust-Region Guided Low-Rank Adaptation for Large Language Models
Paper • 2510.15962 • Published
