[Benchmark Backfill] Integrate Point-Bench into lmms-eval

[Luodian]

Summary

• Integrate new pointbench task with YAML + utils following existing task conventions.
• Load PointArena metadata from data.json, fetch per-sample images via HF datasets-server rows API, and resolve masks from selected_masks.zip.
• Add pointbench_acc point-in-mask scoring and register docs mapping in docs/current_tasks.md.

Validation Evidence

• /Users/luodian/Github/lmms-eval/.venv/bin/python -m lmms_eval --tasks list -> includes pointbench in available tasks.
• /Users/luodian/Github/lmms-eval/.venv/bin/python -m lmms_eval --model dummy_video_reader --model_args response=\"[(500,500)]\",allow_remote=true,fail_on_missing=false --tasks pointbench --limit 8 --batch_size 1 --output_path ./logs/lmm-293-pointbench-smoke -> succeeds with pointbench_acc=0.125.
• /Users/luodian/Github/lmms-eval/.venv/bin/python -m unittest discover -s test/eval -p \"test_cli_parse_args.py\" -> OK.

Tracking

• Closes [Benchmark Backfill] Integrate Point-Bench into lmms-eval #1142
• Linear: LMM-293

Smoke Validation (limit=8)

Status: PASS (LMM-293 / pointbench)

Output Table

Metric	Value
pointbench_acc	0.03125

Sample Output

Sample 1 (doc_id: 0)

• Input: Point to the free space between the person in a black shirt and the car. Your answer should be formatted as a list of tuples, i.e. [(x1, y1), (x2, y2), ...], where each tuple contains the x and y coordinates of a point satisfying the conditions above. The coordinates should be integers between 0 and…
• Model Output: [LMMS_EVAL_REQUEST_FAILED after 5 retries] Error code: 404 - {'error': {'message': 'No endpoints found for google/gemini-flash-1.5.', 'code': 404}, 'user_id': 'user_2sYkuU3dimruZBqpDO0almnSIBN'}
• Reference:
• Scores: N/A
• Tokens: output=0, reasoning=0

Sample 2 (doc_id: 1)

• Input: Point to the tool used for cutting wood. Your answer should be formatted as a list of tuples, i.e. [(x1, y1), (x2, y2), ...], where each tuple contains the x and y coordinates of a point satisfying the conditions above. The coordinates should be integers between 0 and 999, representing the pixel loc…
• Model Output: [LMMS_EVAL_REQUEST_FAILED after 5 retries] Error code: 404 - {'error': {'message': 'No endpoints found for google/gemini-flash-1.5.', 'code': 404}, 'user_id': 'user_2sYkuU3dimruZBqpDO0almnSIBN'}
• Reference:
• Scores: N/A
• Tokens: output=0, reasoning=0

Test Params

uv run python -m lmms_eval --model openai_compatible --model_args "model_version=bytedance-seed/seed-1.6-flash" --tasks pointbench --batch_size 1 --limit 8 --log_samples