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All 4,361 ICLR 2026 papers, including Oral presentations and Outstanding Papers, are now explorable on Papers with Code, grouped by task from 3D generation to GUI agents.
TRINITY is a lightweight 0.6B parameter coordinator that learns to orchestrate multiple LLMs by assigning them roles (Thinker, Worker, Verifier) using an evolutionary strategy. It outperforms individual models and existing coordination methods across coding, math, reasoning, and domain knowledge tasks.
This paper challenges the 'Attention-Confidence Assumption' by demonstrating that attention map sharpness is a poor predictor of correctness in Vision-Language Models. Instead, it shows that reliability is better indicated by hidden-state geometry and self-consistency, with significant findings on architectural differences between late-fusion and early-fusion models.
Researchers from MIT, WPI, and Google propose WRING, a novel post-processing debiasing method for Vision-Language Models that avoids the 'Whac-a-mole dilemma' of amplifying other biases when removing specific ones.
A curated list of approximately 1,200 ICLR 2026 accepted papers (22% of total) with publicly available code, data, or demos has been compiled and published. ICLR 2026 will take place in Rio de Janeiro, Brazil starting April 22nd, 2026.